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Peer-to-Peer (P2P) networks are prominent in the Internet-of-things-assisted industrial environments for distributed computing and smart control systems. The problem arises with the independence and peer systems security due to anonymous access and security measures. In this paper, an innovative control-driven autonomous authentication scheme is proposed for improving the access security of P2P industrial systems. The proposed scheme provides authentication based on P2P system control requirements within its access time. The P2P control systems and their functionalities are provided with classified security measures for administering autonomous security. The advantage of offering autonomous protection is to prevent the sequence of security breaches and control sabotage. In this process, the control system requirements and authentications are paired by identifying the machines' operating time and access time. For identification and grouping-based classification, support vector machines are used. It learns the sabotage and control requirements based on access and control time for providing a rupture-less industrial process. It helps to leverage the detection of autonomous adversaries in P2P industrial control systems. Besides, a less complex and latent-free security measure is achievable using the proposed scheme.
Salem Alkhalaf. A control-driven autonomous authentication scheme for peer-to-peer control systems assisted industrial Internet of things. Soft Computing 2021, 25, 12175 -12189.
AMA StyleSalem Alkhalaf. A control-driven autonomous authentication scheme for peer-to-peer control systems assisted industrial Internet of things. Soft Computing. 2021; 25 (18):12175-12189.
Chicago/Turabian StyleSalem Alkhalaf. 2021. "A control-driven autonomous authentication scheme for peer-to-peer control systems assisted industrial Internet of things." Soft Computing 25, no. 18: 12175-12189.
Social entrepreneurship has recently become a much-desired area of research for academia, practices, and policymaking. Natural or cognitive personal thoughtfulness like loving-kindness meditation (LKM) and compassion trigger individual intentions towards the social entrepreneurial venture. In this process of individual social entrepreneurial intention personality trait plays a very vital role, such as entrepreneurship resilience. For this study, a purposive sampling technique was incorporated and data was collected from 631 business and management sciences students. Data is analyzed by SPSS 23 and for the hypothesis testing, we used the bootstrap analysis of Hayes PROCESS v3.5. This study depicts that LKM has a positive significant impact on compassion and no significant impact on social entrepreneurship intentions while resilience strengthens the direct relationship of compassion with social entrepreneurship and the indirect relationship of LKM with social entrepreneurship via compassion. This study contributes to solving the economic and social problems over the globe especially by boosting the LKM and resilience traits so that the young graduate commence social entrepreneurship. This study helps the academician and policymakers to adopt strategies through which they can encourage youth to indulge in social entrepreneurial ventures solve the social problem and decrease unemployment.
Hameed Sana; Salem Alkhalaf; Salman Zulfiqar; Waleed Al-Rahmi; Ahmad Al-Adwan; Anas AlSoud. Upshots of Intrinsic Traits on Social Entrepreneurship Intentions among Young Business Graduates: An Investigation through Moderated-Mediation Model. Sustainability 2021, 13, 5192 .
AMA StyleHameed Sana, Salem Alkhalaf, Salman Zulfiqar, Waleed Al-Rahmi, Ahmad Al-Adwan, Anas AlSoud. Upshots of Intrinsic Traits on Social Entrepreneurship Intentions among Young Business Graduates: An Investigation through Moderated-Mediation Model. Sustainability. 2021; 13 (9):5192.
Chicago/Turabian StyleHameed Sana; Salem Alkhalaf; Salman Zulfiqar; Waleed Al-Rahmi; Ahmad Al-Adwan; Anas AlSoud. 2021. "Upshots of Intrinsic Traits on Social Entrepreneurship Intentions among Young Business Graduates: An Investigation through Moderated-Mediation Model." Sustainability 13, no. 9: 5192.
Real-time navigation systems rely on multi-object environment information for productive routing and assisted movements of vehicles. The multi-object environment includes infrastructure, neighbours, smart building, and traffic management information for providing assisted driving for the vehicles. The dynamic vehicle environment and sensor failures impact the navigation assistance for the driving users. A robust variance-based information fusion (VIF) technique is proposed in this paper for addressing this issue. The proposed technique makes use of swappable sensor information for fusion for providing reliable navigation assistance. This means the fusion process is performed based on the active sensor information in a decisive manner. For effective fusion with available information, this technique makes use of classification learning. Through this learning process, the error causing information due to sensor failures is identified and mitigated from the fusion. Multi-sensor information classification is performed for performing errorless assistance and decisions. This process is linear throughout the information sensing time intervals for reducing the errors in navigation assistance. The proposed technique's performance is verified using experiments, and the metrics processing time, error, accuracy, and swapping instances are verified.
Salem Alkhalaf. A robust variance information fusion technique for real-time autonomous navigation systems. Measurement 2021, 179, 109441 .
AMA StyleSalem Alkhalaf. A robust variance information fusion technique for real-time autonomous navigation systems. Measurement. 2021; 179 ():109441.
Chicago/Turabian StyleSalem Alkhalaf. 2021. "A robust variance information fusion technique for real-time autonomous navigation systems." Measurement 179, no. : 109441.
Because of the heath measures taken during the outbreak of Covid-19, the lack of educational methods has become the primary concern among educational professionals who have been using technology as a motivational tool. Gamification is very important because it helps students to represent their study contents and enrich their experiences of higher education when learning in-person is unavailable during the Covid-19 period. This study seeks to present an Android-based gamification app to evaluate the effect of using gamification and e-quizzes on college students’ learning. We used the visual blocks language from the MIT App Inventor platform to develop an application, available at (https://play.google.com/store/apps/details?id=appinventor.ai_mekomerofofo.projectGamification). The participants were students from level 2 who used digital lessons for learning MATLAB. The study included gamified learning and non-gamified learning, both integrated into lesson plans, to investigate the differences in learners’ performance. Two types of quizzes were used for instruction: gamified e-quizzes and paper-based quizzes. The outcomes plainly showed that using the new gamified e-quiz was more effective than using paper-based quizzes. They are better for assessing the learning performance of the students in question, specifically in terms of formative assessment. It is very important for instructors to apply games as a modern and innovation-oriented tool through which students can be engaged in an attractive, competitive experience.
Marwa F. Areed; Mohamed A. Amasha; Rania A. Abougalala; Salem Alkhalaf; Dalia Khairy. Developing gamification e-quizzes based on an android app: the impact of asynchronous form. Education and Information Technologies 2021, 1 -22.
AMA StyleMarwa F. Areed, Mohamed A. Amasha, Rania A. Abougalala, Salem Alkhalaf, Dalia Khairy. Developing gamification e-quizzes based on an android app: the impact of asynchronous form. Education and Information Technologies. 2021; ():1-22.
Chicago/Turabian StyleMarwa F. Areed; Mohamed A. Amasha; Rania A. Abougalala; Salem Alkhalaf; Dalia Khairy. 2021. "Developing gamification e-quizzes based on an android app: the impact of asynchronous form." Education and Information Technologies , no. : 1-22.
A.M. Hemeida; S.A. Hassan; Salem Alkhalaf; M.M.M. Mahmoud; M.A. Saber; Ayman M. Bahaa Eldin; Tomonobu Senjyu; Abdullah H. Alayed. Optimizing matrix-matrix multiplication on intel’s advanced vector extensions multicore processor. Ain Shams Engineering Journal 2020, 11, 1179 -1190.
AMA StyleA.M. Hemeida, S.A. Hassan, Salem Alkhalaf, M.M.M. Mahmoud, M.A. Saber, Ayman M. Bahaa Eldin, Tomonobu Senjyu, Abdullah H. Alayed. Optimizing matrix-matrix multiplication on intel’s advanced vector extensions multicore processor. Ain Shams Engineering Journal. 2020; 11 (4):1179-1190.
Chicago/Turabian StyleA.M. Hemeida; S.A. Hassan; Salem Alkhalaf; M.M.M. Mahmoud; M.A. Saber; Ayman M. Bahaa Eldin; Tomonobu Senjyu; Abdullah H. Alayed. 2020. "Optimizing matrix-matrix multiplication on intel’s advanced vector extensions multicore processor." Ain Shams Engineering Journal 11, no. 4: 1179-1190.
This work introduces multi-objective water cycle algorithm (MOWCA) to find the accurate location and size of distributed energy resource (DERs) considering different load models for two seasons (winter, and summer). The impact of uncertainties produced from load and renewable energy resource (RES) such as wind turbine (WT) and photovoltaic (PV) on the performance of the radial distribution system (RDS) are covered as this is closer to the real operation condition. The point estimate method (PEM) is applied for modeling the RES uncertainties. An optimization technique is implemented to find the multi-objective optimal allocation of RESs in RDSs considering uncertainty effect. The main objectives of the work are to maximize the technical, economic and environmental benefits by minimizing different objective functions such as the dissipated power, the voltage deviation, DG cost and total emissions. The proposed multi-objective model is solved by using multi-objective water cycle algorithm (MOWCA), considering the Pareto criterion with nonlinear sorting based on fuzzy mechanism. The proposed algorithm is carried out on different IEEE power systems with various cases.
Ayat Ali Saleh; Tomonobu Senjyu; Salem Alkhalaf; Majed A. Alotaibi; Ashraf M. Hemeida. Water Cycle Algorithm for Probabilistic Planning of Renewable Energy Resource, Considering Different Load Models. Energies 2020, 13, 5800 .
AMA StyleAyat Ali Saleh, Tomonobu Senjyu, Salem Alkhalaf, Majed A. Alotaibi, Ashraf M. Hemeida. Water Cycle Algorithm for Probabilistic Planning of Renewable Energy Resource, Considering Different Load Models. Energies. 2020; 13 (21):5800.
Chicago/Turabian StyleAyat Ali Saleh; Tomonobu Senjyu; Salem Alkhalaf; Majed A. Alotaibi; Ashraf M. Hemeida. 2020. "Water Cycle Algorithm for Probabilistic Planning of Renewable Energy Resource, Considering Different Load Models." Energies 13, no. 21: 5800.
In this paper, we study the number of limit cycles of a new class of polynomial differential systems, which is an extended work of two families of differential systems in systems considered earlier. We obtain the maximum number of limit cycles that bifurcate from the periodic orbits of a center using the averaging theory of first and second order.
Amor Menaceur; Salah Boulaaras; Salem Alkhalaf; Shilpi Jain. Limit Cycles of a Class of Polynomial Differential Systems Bifurcating from the Periodic Orbits of a Linear Center. Symmetry 2020, 12, 1346 .
AMA StyleAmor Menaceur, Salah Boulaaras, Salem Alkhalaf, Shilpi Jain. Limit Cycles of a Class of Polynomial Differential Systems Bifurcating from the Periodic Orbits of a Linear Center. Symmetry. 2020; 12 (8):1346.
Chicago/Turabian StyleAmor Menaceur; Salah Boulaaras; Salem Alkhalaf; Shilpi Jain. 2020. "Limit Cycles of a Class of Polynomial Differential Systems Bifurcating from the Periodic Orbits of a Linear Center." Symmetry 12, no. 8: 1346.
The endless problem of energy supplies are always floating on the surface. As a result, there are a daily improvement to optimize power generators, networks and system configuration. Renewable distributed generators (RDG) are in the heart of these developments. The size of RDG is increasing daily so, it must be optimized to maximize benefits and eliminate drawbacks. Optimization algorithms are one of the fast growing techniques. In this study the Manta Ray Foraging optimization algorithm (MRFO) is applied to minimize power losses through sizing and allocation of DG type I integrated into radial distribution network (RDN). The proposed technique was tested on three different networks, IEEE 33, 69 and 85 test systems. Also, three cases were assumed to evaluate the effectiveness of MRFO algorithm. The results were compared to recent applied techniques.
Mahmoud G. Hemeida; Abdalla Ahmed Ibrahim; Al-Attar A. Mohamed; Salem Alkhalaf; Ayman M. Bahaa El-Dine. Optimal allocation of distributed generators DG based Manta Ray Foraging Optimization algorithm (MRFO). Ain Shams Engineering Journal 2020, 12, 609 -619.
AMA StyleMahmoud G. Hemeida, Abdalla Ahmed Ibrahim, Al-Attar A. Mohamed, Salem Alkhalaf, Ayman M. Bahaa El-Dine. Optimal allocation of distributed generators DG based Manta Ray Foraging Optimization algorithm (MRFO). Ain Shams Engineering Journal. 2020; 12 (1):609-619.
Chicago/Turabian StyleMahmoud G. Hemeida; Abdalla Ahmed Ibrahim; Al-Attar A. Mohamed; Salem Alkhalaf; Ayman M. Bahaa El-Dine. 2020. "Optimal allocation of distributed generators DG based Manta Ray Foraging Optimization algorithm (MRFO)." Ain Shams Engineering Journal 12, no. 1: 609-619.
In primary education, a variety of teaching methods, such as enhanced and discovery learning, have had a significant influence on student achievement, particularly in mathematics. Several studies have discussed the positive effects of the appropriate use of technology in the classroom on student achievement. The main purpose of the current study was to determine the effects of a mobile application on student achievement in a primary school mathematics course in Saudi Arabia. Java was used in the development of the application. The study adopted a quasi-experimental design. The sample comprised 40 students from the Unaizah International School. The data collection instrument was a test in a mathematics course. The test had a reliability of >0.84. The pre- and post-test scores were analyzed with a t-test, which was used to examine the two null hypotheses at the 0.05 level of significance. The findings revealed that mobile applications are more effective than traditional methods for improving student outcomes in mathematics. This indicates the need for support to be provided for such activities in primary school classes. The results further indicate the effectiveness of this current application in developing students’ cognitive skills and improving their mathematical abilities.
Mohamed A. Amasha; Marwa F. Areed; Dalia Khairy; Safaa M. Atawy; Salem Alkhalaf; Rania A. Abougalala. Development of a Java-based Mobile application for mathematics learning. Education and Information Technologies 2020, 26, 945 -964.
AMA StyleMohamed A. Amasha, Marwa F. Areed, Dalia Khairy, Safaa M. Atawy, Salem Alkhalaf, Rania A. Abougalala. Development of a Java-based Mobile application for mathematics learning. Education and Information Technologies. 2020; 26 (1):945-964.
Chicago/Turabian StyleMohamed A. Amasha; Marwa F. Areed; Dalia Khairy; Safaa M. Atawy; Salem Alkhalaf; Rania A. Abougalala. 2020. "Development of a Java-based Mobile application for mathematics learning." Education and Information Technologies 26, no. 1: 945-964.
Manta Ray Foraging Optimization Algorithm (MRFO) is a new bio-inspired, meta-heuristic algorithm. MRFO algorithm has been used for the first time to optimize a multi-objective problem. The best size and location of distributed generations (DG) units have been determined to optimize three different objective functions. Minimization of active power loss, minimization of voltage deviation, and maximization of voltage stability index has been achieved through optimizing DG units under different power factor values, unity, 0.95, 0.866, and optimum value. MRFO has been applied to optimize DGs integrated with two well-known radial distribution power systems: IEEE 33-bus and 69-bus systems. The simulation results have been compared to different optimization algorithms in different cases. The results provide clear evidence of the superiority of MRFO that defind before (Manta Ray Foraging Optimization Algorithm. Quasi-Oppositional Differential Evolution Lévy Flights Algorithm (QODELFA), Stochastic Fractal Search Algorithm (SFSA), Genetics Algorithm (GA), Comprehensive Teaching Learning-Based Optimization (CTLBO), Comprehensive Teaching Learning-Based Optimization (CTLBO (ε constraint)), Multi-Objective Harris Hawks Optimization (MOHHO), Multi-Objective Improved Harris Hawks Optimization (MOIHHO), Multi-Objective Particle Swarm Optimization (MOPSO), and Multi-Objective Particle Swarm Optimization (MOWOA) in terms of power loss, Voltage Stability Index (VSI), and voltage deviation for a wide range of operating conditions. It is clear that voltage buses are improved; and power losses are decreased in both IEEE 33-bus and IEEE 69-bus system for all studied cases. MRFO algorithm gives good results with a smaller number of iterations, which means saving the time required for solving the problem and saving energy. Using the new MRFO technique has a promising future in optimizing different power system problems.
Mahmoud G. Hemeida; Salem Alkhalaf; Al-Attar A. Mohamed; Abdalla Ahmed Ibrahim; Tomonobu Senjyu. Distributed Generators Optimization Based on Multi-Objective Functions Using Manta Rays Foraging Optimization Algorithm (MRFO). Energies 2020, 13, 3847 .
AMA StyleMahmoud G. Hemeida, Salem Alkhalaf, Al-Attar A. Mohamed, Abdalla Ahmed Ibrahim, Tomonobu Senjyu. Distributed Generators Optimization Based on Multi-Objective Functions Using Manta Rays Foraging Optimization Algorithm (MRFO). Energies. 2020; 13 (15):3847.
Chicago/Turabian StyleMahmoud G. Hemeida; Salem Alkhalaf; Al-Attar A. Mohamed; Abdalla Ahmed Ibrahim; Tomonobu Senjyu. 2020. "Distributed Generators Optimization Based on Multi-Objective Functions Using Manta Rays Foraging Optimization Algorithm (MRFO)." Energies 13, no. 15: 3847.
Studies of modified Korteweg-de Vries-type equations are of considerable mathematical interest due to the importance of their applications in various branches of mechanics and physics. In this article, using trilinear estimate in Bourgain spaces, we show the local well-posedness of the initial value problem associated with a coupled system consisting of modified Korteweg-de Vries equations for given data. Furthermore, we prove that the unique solution belongs to Gevrey space G σ × G σ in x and G 3 σ × G 3 σ in t. This article is a continuation of recent studies reflected.
Aissa Boukarou; Kaddour Guerbati; Khaled Zennir; Sultan Alodhaibi; Salem Alkhalaf. Well-Posedness and Time Regularity for a System of Modified Korteweg-de Vries-Type Equations in Analytic Gevrey Spaces. Mathematics 2020, 8, 809 .
AMA StyleAissa Boukarou, Kaddour Guerbati, Khaled Zennir, Sultan Alodhaibi, Salem Alkhalaf. Well-Posedness and Time Regularity for a System of Modified Korteweg-de Vries-Type Equations in Analytic Gevrey Spaces. Mathematics. 2020; 8 (5):809.
Chicago/Turabian StyleAissa Boukarou; Kaddour Guerbati; Khaled Zennir; Sultan Alodhaibi; Salem Alkhalaf. 2020. "Well-Posedness and Time Regularity for a System of Modified Korteweg-de Vries-Type Equations in Analytic Gevrey Spaces." Mathematics 8, no. 5: 809.
This paper deals with the global existence of solutions in a bounded domain for nonlinear viscoelastic Kirchhoff system with a time varying delay by using the energy and Faedo–Galerkin method with respect to the delay term weight condition in the feedback and the delay speed. Furthermore, by using some convex functions properties, we prove a uniform stability estimate.
Nadia Mezouar; Salah Mahmoud Boulaaras; Sultan Alodhaibi; Salem Alkhalaf. Global Existence and Decay of Solutions for Coupled Nondegenerate Kirchhoff System with a Time Varying Delay Term. Complexity 2020, 2020, 1 -20.
AMA StyleNadia Mezouar, Salah Mahmoud Boulaaras, Sultan Alodhaibi, Salem Alkhalaf. Global Existence and Decay of Solutions for Coupled Nondegenerate Kirchhoff System with a Time Varying Delay Term. Complexity. 2020; 2020 ():1-20.
Chicago/Turabian StyleNadia Mezouar; Salah Mahmoud Boulaaras; Sultan Alodhaibi; Salem Alkhalaf. 2020. "Global Existence and Decay of Solutions for Coupled Nondegenerate Kirchhoff System with a Time Varying Delay Term." Complexity 2020, no. : 1-20.
In this paper, by using subsuper solutions method, we study the existence of weak positive solutions for a new class of p,q Laplacian nonlinear elliptic system in bounded domains, when ax, bx,αx, and βx are sign-changing functions that maybe negative near the boundary, without assuming sign conditions on f0,g0,h0, and γ0.
Rafik Guefaifia; Salah Mahmoud Boulaaras; Sultan Alodhaibi; Salem Alkhalaf. Existence of Positive Weak Solutions for a New Class of p,q Laplacian Nonlinear Elliptic System with Sign-Changing Weights. Complexity 2020, 2020, 1 -6.
AMA StyleRafik Guefaifia, Salah Mahmoud Boulaaras, Sultan Alodhaibi, Salem Alkhalaf. Existence of Positive Weak Solutions for a New Class of p,q Laplacian Nonlinear Elliptic System with Sign-Changing Weights. Complexity. 2020; 2020 ():1-6.
Chicago/Turabian StyleRafik Guefaifia; Salah Mahmoud Boulaaras; Sultan Alodhaibi; Salem Alkhalaf. 2020. "Existence of Positive Weak Solutions for a New Class of p,q Laplacian Nonlinear Elliptic System with Sign-Changing Weights." Complexity 2020, no. : 1-6.
Enhancers are DNA fragments that do not encode RNA molecules and proteins, but they act critically in the production of RNAs and proteins by controlling gene expression. Prediction of enhancers and their strength plays significant role in regulating gene expression. Prediction of enhancer regions, in sequences of DNA, is considered a difficult task due to the fact that they are not close to the target gene, have less common motifs and are mostly tissue/cell specific. In recent past, several bioinformatics tools were developed to discriminate enhancers from other regulatory elements and to identify their strengths as well. However the need for improvement in the quality of its prediction method requires enhancements in its application value practically. In this study, we proposed a new method that builds on nucleotide composition and statistical moment based features to distinguish between enhancers and non-enhancers and additionally determine their strength. Our proposed method achieved accuracy better than current state-of-the-art methods using 5-fold and 10-fold cross-validation. The outcomes from our proposed method suggest that the use of statistical moments based features could bear more efficient and effective results. For the accessibility of the scientific community, we have developed a user-friendly web server for EnhancerP-2L which will increase the impact of bioinformatics on medicinal chemistry and drive medical science into an unprecedented resolution. Web server is freely accessible athttp://www.biopred.org/enpred.
Ahmad Hassan Butt; Salem Alkhalaf; Shaukat Iqbal; Yaser Daanial Khan. EnhancerP-2L: A Gene regulatory site identification tool for DNA enhancer region using CREs motifs. 2020, 1 .
AMA StyleAhmad Hassan Butt, Salem Alkhalaf, Shaukat Iqbal, Yaser Daanial Khan. EnhancerP-2L: A Gene regulatory site identification tool for DNA enhancer region using CREs motifs. . 2020; ():1.
Chicago/Turabian StyleAhmad Hassan Butt; Salem Alkhalaf; Shaukat Iqbal; Yaser Daanial Khan. 2020. "EnhancerP-2L: A Gene regulatory site identification tool for DNA enhancer region using CREs motifs." , no. : 1.
This article offers a multi-objective framework for an optimal mix of different types of distributed energy resources (DERs) under different load models. Many renewable and non-renewable energy resources like photovoltaic system (PV), micro-turbine (MT), fuel cell (FC), and wind turbine system (WT) are incorporated in a grid-connected hybrid power system to supply energy demand. The main aim of this article is to maximize environmental, technical, and economic benefits by minimizing various objective functions such as the annual cost, power loss and greenhouse gas emission subject to different power system constraints and uncertainty of renewable energy sources. For each load model, optimum DER size and its corresponding location are calculated. To test the feasibility and validation of the multi-objective water cycle algorithm (MOWCA) is conducted on the IEEE-33 bus and IEEE-69 bus network. The concept of Pareto-optimality is applied to generate trilateral surface of non-dominant Pareto-optimal set followed by a fuzzy decision-making mechanism to obtain the final compromise solution. Multi-objective non-dominated sorting genetic (NSGA-III) algorithm is also implemented and the simulation results between two algorithms are compared with each other. The achieved simulation results evidence the better performance of MOWCA comparing with the NSGA-III algorithm and at different load models, the determined DER locations and size are always righteous for enhancement of the distribution power system performance parameters.
Al-Attar Ali Mohamed; Shimaa Ali; Salem Alkhalaf; Tomonobu Senjyu; Ashraf M. Hemeida. Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm. Sustainability 2019, 11, 6550 .
AMA StyleAl-Attar Ali Mohamed, Shimaa Ali, Salem Alkhalaf, Tomonobu Senjyu, Ashraf M. Hemeida. Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm. Sustainability. 2019; 11 (23):6550.
Chicago/Turabian StyleAl-Attar Ali Mohamed; Shimaa Ali; Salem Alkhalaf; Tomonobu Senjyu; Ashraf M. Hemeida. 2019. "Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm." Sustainability 11, no. 23: 6550.
Data mining optimization received much attention in the last decades due to introducing new optimization techniques, which were applied successfully to solve such stochastic mining problems. This paper addresses implementation of evolutionary optimization algorithms (EOAs) for mining two famous data sets in machine learning by implementing four different optimization techniques. The selected data sets used for evaluating the proposed optimization algorithms are Iris dataset and Breast Cancer dataset. In the classification problem of this paper, the neural network (NN) is used with four optimization techniques, which are whale optimization algorithm (WOA), dragonfly algorithm (DA), multiverse optimization (MVA), and grey wolf optimization (GWO). Different control parameters were considered for accurate judgments of the suggested optimization techniques. The comparitive study proves that, the GWO, and MVO provide accurate results over both WO, and DA in terms of convergence, runtime, classification rate, and MSE.
Mohamed Eid; Salem Alkhalaf; A. Mady; E.A. Mahmoud; M.E. Hussein; Ayman M. Baha Eldin. Implementation of nature-inspired optimization algorithms in some data mining tasks. Ain Shams Engineering Journal 2019, 11, 309 -318.
AMA StyleMohamed Eid, Salem Alkhalaf, A. Mady, E.A. Mahmoud, M.E. Hussein, Ayman M. Baha Eldin. Implementation of nature-inspired optimization algorithms in some data mining tasks. Ain Shams Engineering Journal. 2019; 11 (2):309-318.
Chicago/Turabian StyleMohamed Eid; Salem Alkhalaf; A. Mady; E.A. Mahmoud; M.E. Hussein; Ayman M. Baha Eldin. 2019. "Implementation of nature-inspired optimization algorithms in some data mining tasks." Ain Shams Engineering Journal 11, no. 2: 309-318.
This work outlines a novel technique for optimization, which stems from the composition of two random distributions: Maxwell and Gaussian, so-called Maxwell Gaussian Algorithm (MGA). The proposed algorithm tends to find the optimum elements of traditional PI controllers for the PMSG-based WECS, in a manner whereby the optimal dynamic performance of PMSG through another grid fault and operation could be achieved easily. In order to realize an optimum search, Maxwell-Gaussian distribution is employed to control the standard deviation of Gaussian normal in addition to a new selection of the mating solutions with adaptive manner control. Furthermore, four different updating equations were created for the purpose of generating the given solution to increase the exploration over research space. MGA-based coordinate control strategy is implemented in the machine side converter (MSC) and grid side converter (GSC). The MGA is compared with the different optimization techniques such as the Ant Lion Optimizer (ALO) and Satin bowerbird optimizer (SBO). In order to ensure the robustness of the proposed algorithm, four case studies namely; step change of wind speed, variables of wind speed, Random wind speed variation and three phase symmetrical faults. The simulation results indicate the superiority of the proposed algorithm over other used optimization techniques.
Al-Attar Mohamed; A.L. Haridy; T. Senjyu; Hany M. Hasanien; Salem Alkhalaf; A.M. Hemeida. WITHDRAWN: PMSG driven by wind energy controller based Maxwell-Gaussian optimization technique. Ain Shams Engineering Journal 2019, 1 .
AMA StyleAl-Attar Mohamed, A.L. Haridy, T. Senjyu, Hany M. Hasanien, Salem Alkhalaf, A.M. Hemeida. WITHDRAWN: PMSG driven by wind energy controller based Maxwell-Gaussian optimization technique. Ain Shams Engineering Journal. 2019; ():1.
Chicago/Turabian StyleAl-Attar Mohamed; A.L. Haridy; T. Senjyu; Hany M. Hasanien; Salem Alkhalaf; A.M. Hemeida. 2019. "WITHDRAWN: PMSG driven by wind energy controller based Maxwell-Gaussian optimization technique." Ain Shams Engineering Journal , no. : 1.
Maximizing the classification accuracy and minimizing the number of selected features are the two main incompatible objectives for using feature selection to overcome the curse of dimensionality. “Classification accuracy highly dependents on the nature of the features in a dataset which may contain irrelevant or redundant data. The main aim of feature selection is to eliminate these types of features to enhance the classification accuracy.” This work presents a new meta-heuristic optimization approach, called Parasitism-Predation Algorithm (PPA), which mimics the interaction between the predator (cats), the parasite (cuckoos) and the host (crows) in the crow–cuckoo–cat system model to overcome the problems of low convergence and the curse of dimensionality of large data. The proposed hybrid framework combines the relative advantages of cat swarm optimization (CSO), cuckoo search (CS) and crow search algorithm (CSA) to attain a combinatorial set of features to boost up the classification accuracy. Nesting, parasitism, and predation phases are supposed to help exploration ability and balance in the context of solving classification problems. In addition, Levy flight distribution is applied to help better diversity of conventional CSA and improve ability of exploration. Meanwhile, an effective fitness function is utilized to enable the proposed PPA-based feature selector using K-Nearest Neighbors algorithm (KNN) to attain a combinatorial set of features. The proposed PPA and four standard heuristic search algorithms are looked at to gauge how efficient the proposed option is. Additionally, eighteen classification datasets are deployed to gauges its efficacy. The results highlight that the algorithm proposed is both effective and competitive in terms of performance of classification and dimensionality reduction as opposed to other heuristic options.
Al-Attar A. Mohamed; S.A. Hassan; A.M. Hemeida; Salem Alkhalaf; M.M.M. Mahmoud; Ayman M. Baha Eldin. Parasitism – Predation algorithm (PPA): A novel approach for feature selection. Ain Shams Engineering Journal 2019, 11, 293 -308.
AMA StyleAl-Attar A. Mohamed, S.A. Hassan, A.M. Hemeida, Salem Alkhalaf, M.M.M. Mahmoud, Ayman M. Baha Eldin. Parasitism – Predation algorithm (PPA): A novel approach for feature selection. Ain Shams Engineering Journal. 2019; 11 (2):293-308.
Chicago/Turabian StyleAl-Attar A. Mohamed; S.A. Hassan; A.M. Hemeida; Salem Alkhalaf; M.M.M. Mahmoud; Ayman M. Baha Eldin. 2019. "Parasitism – Predation algorithm (PPA): A novel approach for feature selection." Ain Shams Engineering Journal 11, no. 2: 293-308.
In this paper, the performance of different optimization techniques namely, multi-objective dragonfly algorithm (MODA) and multi-objective differential evolution (MODE) are presented and compared. The uncertainty effect of a wind turbine (WT) on the performance of the distribution system is taken into account. The point estimate method (PEM) is used to model the uncertainty in wind power. Optimization methods are applied to determine the multi-objective optimal allocation of distributed generation (DG) in radial distribution systems at a different load level (light, normal, heavy load level). The multi-objective function is expressed to minimize the total power loss, total operating cost, and improve the voltage stability index of the radial distribution system (RDS). Multi-objective proposed algorithms are used to generate the Pareto optimal solutions; and a fuzzy decision-making function is used to produce a hybrid function for obtaining the best compromise solution. The proposed algorithms are carried out on 33-bus and IEEE-69-bus power systems. The simulation results show the effectiveness of installing the proper size of DG at the suitable location based on different techniques.
Salem Alkhalaf; Tomonobu Senjyu; Ayat Ali Saleh; Ashraf M. Hemeida; Al-Attar Ali Mohamed. A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels. Sustainability 2019, 11, 5323 .
AMA StyleSalem Alkhalaf, Tomonobu Senjyu, Ayat Ali Saleh, Ashraf M. Hemeida, Al-Attar Ali Mohamed. A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels. Sustainability. 2019; 11 (19):5323.
Chicago/Turabian StyleSalem Alkhalaf; Tomonobu Senjyu; Ayat Ali Saleh; Ashraf M. Hemeida; Al-Attar Ali Mohamed. 2019. "A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels." Sustainability 11, no. 19: 5323.
The current paper introduces a realistic solution for energy demand in Makadi Bay, Red-Sea, Hurgada, Egypt using energy system crossbred of Renewable Wind Energy System (WES) and Photovoltaic System (PVS) in the presence of Battery Energy Storage (BES). A real measurement for wind speed was recorded through a year of 2017. Also, the sun irradiance and temperature were recorded through the same period, to be considered for the output power calculations from the proposed crossbred renewable energy system. The demand load data for the city was recoded as well as through the same period for evaluating the feasibility of the system if it can cover the city loads. Linear TORSCHE optimization technique has utilized to reach an optimum solution of the proposed crossbred renewable energy system. Individual configuration of PVS & WES in presence of BES have been studied and compared with the hybrid PV/WT. Furthermore, economic analysis has presented to prove the best economical system. The obtained results show that installing such hybrid system consists of WES, PVS and BES is cheaper than installing each one individually.
A.M. Hemeida; M.H. El-Ahmar; A.M. El-Sayed; Hany M. Hasanien; Salem Alkhalaf; M.F.C. Esmail; T. Senjyu. Optimum design of hybrid wind/PV energy system for remote area. Ain Shams Engineering Journal 2019, 11, 11 -23.
AMA StyleA.M. Hemeida, M.H. El-Ahmar, A.M. El-Sayed, Hany M. Hasanien, Salem Alkhalaf, M.F.C. Esmail, T. Senjyu. Optimum design of hybrid wind/PV energy system for remote area. Ain Shams Engineering Journal. 2019; 11 (1):11-23.
Chicago/Turabian StyleA.M. Hemeida; M.H. El-Ahmar; A.M. El-Sayed; Hany M. Hasanien; Salem Alkhalaf; M.F.C. Esmail; T. Senjyu. 2019. "Optimum design of hybrid wind/PV energy system for remote area." Ain Shams Engineering Journal 11, no. 1: 11-23.