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Oscar Castillo holds a Doctor in Science degree (Doctor Habilitatus) in Computer Science from the Polish Academy of Sciences (with the dissertation “Soft Computing and Fractal Theory for Intelligent Manufacturing”). He is a Professor of Computer Science in the Graduate Division, Tijuana Institute of Technology, Tijuana, Mexico. In addition, he is serving as Research Director of Computer Science and head of the research group on Hybrid Fuzzy Intelligent Systems. Currently, he is President of HAFSA (Hispanic American Fuzzy Systems Association) and the past President of IFSA (International Fuzzy Systems Association). Prof. Castillo is also Chair of the Mexican Chapter of the Computational Intelligence Society (IEEE). He also belongs to the Technical Committee on Fuzzy Systems of IEEE and to the Task Force on “Extensions to Type-1 Fuzzy Systems”. He is also a member of NAFIPS, IFSA, and IEEE. He belongs to the Mexican Research System (SNI Level 3). His research interests are in Type-2 Fuzzy Logic, Fuzzy Control, Neuro-Fuzzy, and Genetic-Fuzzy hybrid approaches. He has published over 300 journal papers, 10 authored books, 40 edited books, 200 papers in conference proceedings, and more than 300 chapters in edited books, with a total of 980 publications, according to Scopus (H index=66, and more than 1050 publications, according to Research Gate (H index=80 in Google Scholar).
This work is mainly focused on improving the differential evolution algorithm with the utilization of shadowed and general type 2 fuzzy systems to dynamically adapt one of the parameters of the evolutionary method. Previously, we have worked with both kinds of fuzzy systems in different types of benchmark problems and it has been found that the use of fuzzy logic in combination with the differential evolution algorithm gives good results. In some of the studies, it is clearly shown that, when compared to other algorithms, our methodology turns out to be statistically better. In this case, the mutation parameter is dynamically moved during the evolution process by using shadowed and general type-2 fuzzy systems. The main contribution of this work is the ability to determine, through experimentation in a benchmark control problem, which of the two kinds of the used fuzzy systems has better results when combined with the differential evolution algorithm. This is because there are no similar works to our proposal in which shadowed and general type 2 fuzzy systems are used and compared. Moreover, to validate the performance of both fuzzy systems, a noise level is used in the controller, which simulates the disturbances that may exist in the real world and is thus able to validate statistically if there are significant differences between shadowed and general type 2 fuzzy systems.
Patricia Ochoa; Oscar Castillo; Patricia Melin; José Soria. Differential Evolution with Shadowed and General Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Optimal Design of Fuzzy Controllers. Axioms 2021, 10, 194 .
AMA StylePatricia Ochoa, Oscar Castillo, Patricia Melin, José Soria. Differential Evolution with Shadowed and General Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Optimal Design of Fuzzy Controllers. Axioms. 2021; 10 (3):194.
Chicago/Turabian StylePatricia Ochoa; Oscar Castillo; Patricia Melin; José Soria. 2021. "Differential Evolution with Shadowed and General Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Optimal Design of Fuzzy Controllers." Axioms 10, no. 3: 194.
Nowadays, in a competitive market circumstance, a distributor/wholesaler permits a settled trade credit to the retailer(s) for more deal, and in turn, retailer offers a fraction of that credit period to the customers for the quick-moving of the business, i.e. to increase the demand. In reality, all the customers are not fully trustworthy. There are some customers who do not pay the dues after enjoying the trade credit. The number of default customers increases with the increase in trade credit period given to them. Thus, these two contradict each other. There is a decent market with increasing demand for greener (contamination free) item(s), especially for deteriorating item(s). Here, in the present investigation, customers’ demand increases with both the trade credit given to customers and the greenness of the product. Obviously, the price tag will be higher for green items. Increased price always negates the demand. Hence, greenness and the increased price of the green products are contradictory to each other. Once more, to reduce the deterioration rate, the retailer incurs an expenditure termed as preservation technology cost. Due to preservation, deterioration of the items decreases but cost increases. Here, control of deterioration and preservation act contradictory to each other. The base demand, effects (coefficients) of the trade credit, and greenness are taken as fuzzy. Incorporating the above facts, a model is developed with a fuzzy differential equation and solved by Chalco-Cano \(\alpha \)-cut method. The profit is calculated by assuming two-level trade credit and default customers. In this investigation, a new concept of clearing the supplier’s dues is introduced. Instead of payment of all dues at the end of business cycle period, the retailer clears his dues as and when he has sufficient money for this purpose. Numerical experiments for different cases are performed along with their physical interpretations. Imprecise nature of the profit is shown through its membership function and depicted graphically. Interestingly, it is demonstrated that positive effect of deterioration due to the increase in preservation technology and increase in profit due to greenness are up to certain extent. After that, these have the reverse effects.
Anindita Kundu; Partha Guchhait; Manoranjan Maiti; Oscar Castillo. Inventory of a deteriorating green product with preservation technology cost using a hybrid algorithm. Soft Computing 2021, 25, 11621 -11636.
AMA StyleAnindita Kundu, Partha Guchhait, Manoranjan Maiti, Oscar Castillo. Inventory of a deteriorating green product with preservation technology cost using a hybrid algorithm. Soft Computing. 2021; 25 (17):11621-11636.
Chicago/Turabian StyleAnindita Kundu; Partha Guchhait; Manoranjan Maiti; Oscar Castillo. 2021. "Inventory of a deteriorating green product with preservation technology cost using a hybrid algorithm." Soft Computing 25, no. 17: 11621-11636.
In this article, the evolution in both space and time of the COVID-19 pandemic is studied by utilizing a neural network with a self-organizing nature for the spatial analysis of data, and a fuzzy fractal method for capturing the temporal trends of the time series of the countries considered in this study. Self-organizing neural networks possess the capability to cluster countries in the space domain based on their similar characteristics, with respect to their COVID-19 cases. This form enables the finding of countries that have a similar behavior, and thus can benefit from utilizing the same methods in fighting the virus propagation. In order to validate the approach, publicly available datasets of COVID-19 cases worldwide have been used. In addition, a fuzzy fractal approach is utilized for the temporal analysis of the time series of the countries considered in this study. Then, a hybrid combination, using fuzzy rules, of both the self-organizing maps and the fuzzy fractal approach is proposed for efficient coronavirus disease 2019 (COVID-19) forecasting of the countries. Relevant conclusions have emerged from this study that may be of great help in putting forward the best possible strategies in fighting the virus pandemic. Many of the existing works concerned with COVID-19 look at the problem mostly from a temporal viewpoint, which is of course relevant, but we strongly believe that the combination of both aspects of the problem is relevant for improving the forecasting ability. The main idea of this article is combining neural networks with a self-organizing nature for clustering countries with a high similarity and the fuzzy fractal approach for being able to forecast the times series. Simulation results of COVID-19 data from countries around the world show the ability of the proposed approach to first spatially cluster the countries and then to accurately predict in time the COVID-19 data for different countries with a fuzzy fractal approach.
Patricia Melin; Oscar Castillo. Spatial and Temporal Spread of the COVID-19 Pandemic Using Self Organizing Neural Networks and a Fuzzy Fractal Approach. Sustainability 2021, 13, 8295 .
AMA StylePatricia Melin, Oscar Castillo. Spatial and Temporal Spread of the COVID-19 Pandemic Using Self Organizing Neural Networks and a Fuzzy Fractal Approach. Sustainability. 2021; 13 (15):8295.
Chicago/Turabian StylePatricia Melin; Oscar Castillo. 2021. "Spatial and Temporal Spread of the COVID-19 Pandemic Using Self Organizing Neural Networks and a Fuzzy Fractal Approach." Sustainability 13, no. 15: 8295.
This article is presenting a first attempt on a proposed fuzzy fractal control method for efficiently controlling nonlinear dynamic systems. The main goal is to combine the main advantages of fractal theoretical concepts and fuzzy logic theory for achieving efficient control of nonlinear dynamic systems. The concept coming from Fractal theory, known as the fractal dimension, can be utilized to measure the complexity of the dynamic behavior of a non-linear plant. On the other hand, fuzzy logic theory can be used to represent and capture the expert knowledge in controlling a plant. In addition, fuzzy logic enables to manage the uncertainty involved in the decision-making process for achieving efficient control of a non-linear plant. We illustrate the proposed fuzzy fractal control method with the current worldwide situation that requires achieving an efficient control of the COVID-19 pandemics.
Oscar Castillo; Patricia Melin. A new fuzzy fractal control approach of non-linear dynamic systems: The case of controlling the COVID-19 pandemics. Chaos, Solitons & Fractals 2021, 151, 111250 .
AMA StyleOscar Castillo, Patricia Melin. A new fuzzy fractal control approach of non-linear dynamic systems: The case of controlling the COVID-19 pandemics. Chaos, Solitons & Fractals. 2021; 151 ():111250.
Chicago/Turabian StyleOscar Castillo; Patricia Melin. 2021. "A new fuzzy fractal control approach of non-linear dynamic systems: The case of controlling the COVID-19 pandemics." Chaos, Solitons & Fractals 151, no. : 111250.
This article describes the application of a variant of the shark smell optimization (VSSO) biological inspired algorithm in the optimal design of a type-2 fuzzy controller. We show how the performance of VSSO is based on the frontal and rotational movement of the shark when navigating a dimensional search domain, which is based on the food-seeking behavior of sharks. The optimization of the design of a Mamdani interval type-2 fuzzy controller (IT2-FLC) applying VSSO is also described. The optimized controller is tested with the navigation of an autonomous mobile robot (AMR) in an unknown and changing environment. This work was developed as follows: first, the VSSO algorithm is improved by adjusting its main alpha and beta parameters with a fuzzy system, later the parameter values of the fuzzy controller input/output membership functions are optimized. Finally, a comparison is made between the results of type-1 (T1) and interval type-2 fuzzy controllers applying the proposed methodology. When comparing the T1 and IT2-FLC controllers, the application of the VSSO algorithm in T1-FLC shows good performance in robot navigation; however, IT2-FLC presents better performance due to its ability to handle higher levels of uncertainty. The performance evaluation of the proposed method and its application in different navigation problems has been carried out through computer simulations using Matlab-Simulink.
Felizardo Cuevas; Oscar Castillo; Prometeo Cortes. Optimal Setting of Membership Functions for Interval Type-2 Fuzzy Tracking Controllers Using a Shark Smell Metaheuristic Algorithm. International Journal of Fuzzy Systems 2021, 1 -24.
AMA StyleFelizardo Cuevas, Oscar Castillo, Prometeo Cortes. Optimal Setting of Membership Functions for Interval Type-2 Fuzzy Tracking Controllers Using a Shark Smell Metaheuristic Algorithm. International Journal of Fuzzy Systems. 2021; ():1-24.
Chicago/Turabian StyleFelizardo Cuevas; Oscar Castillo; Prometeo Cortes. 2021. "Optimal Setting of Membership Functions for Interval Type-2 Fuzzy Tracking Controllers Using a Shark Smell Metaheuristic Algorithm." International Journal of Fuzzy Systems , no. : 1-24.
In this article, the evolution in space and in time of the coronavirus pandemic is studied by utilizing a neural network with a self-organizing nature for the spatial analysis of data, and a fuzzy fractal method for capturing the temporal trends of the time series of the countries. Self-organizing neural networks possess the capability for clustering countries in the space domain based on their similar characteristics with respect to their coronavirus cases. In this form enabling finding the countries that are having similar behavior and thus can benefit from utilizing the same methods in fighting the virus propagation. To validate the approach, publicly available datasets of coronavirus cases worldwide have been used. In addition, a fuzzy fractal approach is utilized for the temporal analysis of time series of the countries. Then, a hybrid combination of both the self-organizing maps and the fuzzy fractal approach is proposed for efficient COVID-19 forecasting of the countries. Relevant conclusions have emerged from this study, that may be of great help in putting forward the best possible strategies in fighting the virus pandemic. A lot of the existing works concerned with the Coronavirus have look at the problem mostly from the temporal viewpoint that is of course relevant, but we strongly believe that the combination of both aspects of the problem is relevant to improve the forecasting ability. The most relevant contribution of this article is the proposal of combining neural networks with a self-organizing nature for clustering countries with high similarity and the fuzzy fractal approach for being able to forecast the times series and help in planning control actions for the Coronavirus pandemic.
Patricia Melin; Oscar Castillo. Spatial and Temporal Spread of the Coronavirus Pandemic using Self Organizing Neural Networks and a Fuzzy Fractal Approach. 2021, 1 .
AMA StylePatricia Melin, Oscar Castillo. Spatial and Temporal Spread of the Coronavirus Pandemic using Self Organizing Neural Networks and a Fuzzy Fractal Approach. . 2021; ():1.
Chicago/Turabian StylePatricia Melin; Oscar Castillo. 2021. "Spatial and Temporal Spread of the Coronavirus Pandemic using Self Organizing Neural Networks and a Fuzzy Fractal Approach." , no. : 1.
Zika virus is amongst the deadly viruses still prevalent in more than 50 countries around the world. It is amosquitoes-borne disease that spread at fast rate in 2016. Zika virus belongs to the family of Flaviviridae virus. In this paper, a deterministic mathematical model is formulated to investigate the effects of vaccination in controlling the disease through optimal solution. The qualitative behavior of the proposed model is studied by using the theory of stability analysis. A basic reproduction number is computed by using Next Generation Technique todecide a threshold values of R0i.e. if R01 dynamicsthe system is locally asymptotically unstable and diseases persist in the system. The global stability is also investigated via Lyapunov function. Numerical results were performed to see the effects of vaccination on the dynamics of the model with and without optimal interventions. The analysis of model suggests various strategies which help in the elimination of the disease.
Naveen Sharma; Ram Singh; Jagdev Singh; Oscar Castillo. Modeling assumptions, optimal control strategies and mitigation through vaccination to Zika virus. Chaos, Solitons & Fractals 2021, 150, 111137 .
AMA StyleNaveen Sharma, Ram Singh, Jagdev Singh, Oscar Castillo. Modeling assumptions, optimal control strategies and mitigation through vaccination to Zika virus. Chaos, Solitons & Fractals. 2021; 150 ():111137.
Chicago/Turabian StyleNaveen Sharma; Ram Singh; Jagdev Singh; Oscar Castillo. 2021. "Modeling assumptions, optimal control strategies and mitigation through vaccination to Zika virus." Chaos, Solitons & Fractals 150, no. : 111137.
This work is mainly focused on improving the differential evolution algorithm with the utilization of shadowed and general type 2 fuzzy systems to dynamically adapt one of the parameters of the evolutionary method. In this case, the mutation parameter is dynamically moved during the evolution process by using a shadowed and general type-2 fuzzy systems. The main idea of this work is to make a performance comparison between using shadowed and general type 2 fuzzy systems as controllers of the mutation parameter in differential evolution. The performance is compared with the problem of optimizing fuzzy controllers for a D.C. Motor. Simulation results show that general type-2 fuzzy systems are better when higher levels of noise are considered in the controller.
Patricia Ochoa; Oscar Castillo; Patricia Melin; José Soria. Differential Evolution With Shadowed and General Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Optimal Design of Fuzzy Controllers. 2021, 1 .
AMA StylePatricia Ochoa, Oscar Castillo, Patricia Melin, José Soria. Differential Evolution With Shadowed and General Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Optimal Design of Fuzzy Controllers. . 2021; ():1.
Chicago/Turabian StylePatricia Ochoa; Oscar Castillo; Patricia Melin; José Soria. 2021. "Differential Evolution With Shadowed and General Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Optimal Design of Fuzzy Controllers." , no. : 1.
One of the most studied application areas of intelligent systems is the classification area, and this is because classification covers a wide range of real-world problems. Some examples are fault-diagnosis, image segmentation, medical diagnosis, among others. In most cases, the intelligent systems designed for the solution of this kind of problems are based on supervised learning, which is based on learning how to classify with previous datasets for finding relations between the inputs and outputs. The main focus of the present paper is the supervised generation of general type-2 fuzzy classifiers with a new strategy for modeling data uncertainty. The proposed methodology includes a mix of concepts, such as the use of embedded type-1 membership functions, statistical concepts such as the quartiles, and nature inspired optimization methods. The classifiers generated with the proposed methodology are compared with respect to other general type-2 fuzzy classifiers based on symmetric uncertainty to evaluate their performance, in this way obtaining interesting results for medical diagnosis with benchmark data sets.
Emanuel Ontiveros-Robles; Oscar Castillo; Patricia Melin. Towards asymmetric uncertainty modeling in designing General Type-2 Fuzzy classifiers for medical diagnosis. Expert Systems with Applications 2021, 183, 115370 .
AMA StyleEmanuel Ontiveros-Robles, Oscar Castillo, Patricia Melin. Towards asymmetric uncertainty modeling in designing General Type-2 Fuzzy classifiers for medical diagnosis. Expert Systems with Applications. 2021; 183 ():115370.
Chicago/Turabian StyleEmanuel Ontiveros-Robles; Oscar Castillo; Patricia Melin. 2021. "Towards asymmetric uncertainty modeling in designing General Type-2 Fuzzy classifiers for medical diagnosis." Expert Systems with Applications 183, no. : 115370.
Oscar Castillo; Pranab Kumar Muhuri; Hong Mo; Chengdong Li; Runmei Li; Hamid Reza Karimi. Editorial on Special Issue: “Trends and Developments on Type-2 Fuzzy Sets and Systems”. International Journal of Fuzzy Systems 2021, 23, 1055 -1056.
AMA StyleOscar Castillo, Pranab Kumar Muhuri, Hong Mo, Chengdong Li, Runmei Li, Hamid Reza Karimi. Editorial on Special Issue: “Trends and Developments on Type-2 Fuzzy Sets and Systems”. International Journal of Fuzzy Systems. 2021; 23 (4):1055-1056.
Chicago/Turabian StyleOscar Castillo; Pranab Kumar Muhuri; Hong Mo; Chengdong Li; Runmei Li; Hamid Reza Karimi. 2021. "Editorial on Special Issue: “Trends and Developments on Type-2 Fuzzy Sets and Systems”." International Journal of Fuzzy Systems 23, no. 4: 1055-1056.
As can be observed in the experimental results, some specific T2 FDS proposed with our methodology
Patricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. Discussion of Results. Self-Powered and Soft Polymer MEMS/NEMS Devices 2021, 73 -75.
AMA StylePatricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo. Discussion of Results. Self-Powered and Soft Polymer MEMS/NEMS Devices. 2021; ():73-75.
Chicago/Turabian StylePatricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. 2021. "Discussion of Results." Self-Powered and Soft Polymer MEMS/NEMS Devices , no. : 73-75.
Nowadays, one of the most important applications of intelligent systems are expert systems for decision making, these kinds of systems can provide experts with a tool for expert systems.
Patricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. Introduction. Self-Powered and Soft Polymer MEMS/NEMS Devices 2021, 1 -3.
AMA StylePatricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo. Introduction. Self-Powered and Soft Polymer MEMS/NEMS Devices. 2021; ():1-3.
Chicago/Turabian StylePatricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. 2021. "Introduction." Self-Powered and Soft Polymer MEMS/NEMS Devices , no. : 1-3.
In this chapter the theoretical elements necessary to the development of the proposed approach and methodologies are introduced.
Patricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. Background and Theory. Self-Powered and Soft Polymer MEMS/NEMS Devices 2021, 5 -28.
AMA StylePatricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo. Background and Theory. Self-Powered and Soft Polymer MEMS/NEMS Devices. 2021; ():5-28.
Chicago/Turabian StylePatricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. 2021. "Background and Theory." Self-Powered and Soft Polymer MEMS/NEMS Devices , no. : 5-28.
In the present work, it was proposed a methodology for the automatic design of Fuzzy.
Patricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. Conclusions. Self-Powered and Soft Polymer MEMS/NEMS Devices 2021, 77 -78.
AMA StylePatricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo. Conclusions. Self-Powered and Soft Polymer MEMS/NEMS Devices. 2021; ():77-78.
Chicago/Turabian StylePatricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. 2021. "Conclusions." Self-Powered and Soft Polymer MEMS/NEMS Devices , no. : 77-78.
The present chapter presents the proposed methodology for the design of General Type-2 Fuzzy Inference Systems for diagnosis problems.
Patricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. Proposed Methodology. Self-Powered and Soft Polymer MEMS/NEMS Devices 2021, 29 -62.
AMA StylePatricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo. Proposed Methodology. Self-Powered and Soft Polymer MEMS/NEMS Devices. 2021; ():29-62.
Chicago/Turabian StylePatricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. 2021. "Proposed Methodology." Self-Powered and Soft Polymer MEMS/NEMS Devices , no. : 29-62.
In this chapter the results obtained for the previously presented approaches are presented, in order to compare the developed systems based on the performance measured with the accuracy.
Patricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. Experimental Results. Self-Powered and Soft Polymer MEMS/NEMS Devices 2021, 63 -72.
AMA StylePatricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo. Experimental Results. Self-Powered and Soft Polymer MEMS/NEMS Devices. 2021; ():63-72.
Chicago/Turabian StylePatricia Melin; Emanuel Ontiveros-Robles; Oscar Castillo. 2021. "Experimental Results." Self-Powered and Soft Polymer MEMS/NEMS Devices , no. : 63-72.
This paper presents a method for creating Forex market predictive models using multi-agent and fuzzy systems, which have the objective of simulating the interactions that provoke changes in the price. Agents in the system represent traders performing buy and sell orders in a market, and fuzzy systems are used to model the rules followed by traders performing trades in a live market and intuitionistic fuzzy logic to model their decisions’ indeterminacy. We use functions to restrict the agents’ decisions, which make the agents become specialized at particular market conditions. These “specialization” functions use the grades of membership obtained from an agent’s fuzzy system and thresholds obtained from training data sets, to determine if that agent is specialized enough to handle a market’s current conditions. We have performed experiments and compared against the state of the art. Results demonstrate that our method obtains predictive errors (using mean absolute error) that are in the same order of magnitude than those errors obtained by models generated using deep learning and models generated by random forest, AdaBoost, XGBoost, and support-vector machines. Furthermore, we performed experiments that show that identifying specialized agents yields better results.
Amaury Hernandez-Aguila; Mario Garcia-Valdez; Juan-Julian Merelo-Guervos; Manuel Castanon-Puga; Oscar Castillo Lopez. Using Fuzzy Inference Systems for the Creation of Forex Market Predictive Models. IEEE Access 2021, 9, 69391 -69404.
AMA StyleAmaury Hernandez-Aguila, Mario Garcia-Valdez, Juan-Julian Merelo-Guervos, Manuel Castanon-Puga, Oscar Castillo Lopez. Using Fuzzy Inference Systems for the Creation of Forex Market Predictive Models. IEEE Access. 2021; 9 ():69391-69404.
Chicago/Turabian StyleAmaury Hernandez-Aguila; Mario Garcia-Valdez; Juan-Julian Merelo-Guervos; Manuel Castanon-Puga; Oscar Castillo Lopez. 2021. "Using Fuzzy Inference Systems for the Creation of Forex Market Predictive Models." IEEE Access 9, no. : 69391-69404.
In this paper, a novel control approach is proposed for a class of uncertain nonlinear system with unmodeled dynamics. Each output of the system is modeled by several first-order dynamic fractional-order fuzzy systems. The best dynamic model is selected at a period of time and the control signal is designed based on this model. The dynamic fractional-order models are based on the special case of general type-2 fuzzy systems which are called interval type-3 fuzzy logic systems (IT3FLSs). The adaptation laws for the consequent parameters of IT3FLSs are derived through stability analysis of the fractional-order systems based on the linear matrix inequality approach. The effectiveness of the proposed scheme is verified by normal simulation on the hyperchaotic Lorenz system with unmodeled dynamics, real-time simulation on the chaotic model of the brushless DC motors using Arduino boards and experimental examination on a heat transfer system with fully unknown dynamics.
Ardashir Mohammadzadeh; Oscar Castillo; Shahab S. Band; Amirhosein Mosavi. A Novel Fractional-Order Multiple-Model Type-3 Fuzzy Control for Nonlinear Systems with Unmodeled Dynamics. International Journal of Fuzzy Systems 2021, 1 -19.
AMA StyleArdashir Mohammadzadeh, Oscar Castillo, Shahab S. Band, Amirhosein Mosavi. A Novel Fractional-Order Multiple-Model Type-3 Fuzzy Control for Nonlinear Systems with Unmodeled Dynamics. International Journal of Fuzzy Systems. 2021; ():1-19.
Chicago/Turabian StyleArdashir Mohammadzadeh; Oscar Castillo; Shahab S. Band; Amirhosein Mosavi. 2021. "A Novel Fractional-Order Multiple-Model Type-3 Fuzzy Control for Nonlinear Systems with Unmodeled Dynamics." International Journal of Fuzzy Systems , no. : 1-19.
Stochastic fractal search (SFS) is a novel method inspired by the process of stochastic growth in nature and the use of the fractal mathematical concept. Considering the chaotic stochastic diffusion property, an improved dynamic stochastic fractal search (DSFS) optimization algorithm is presented. The DSFS algorithm was tested with benchmark functions, such as the multimodal, hybrid, and composite functions, to evaluate the performance of the algorithm with dynamic parameter adaptation with type-1 and type-2 fuzzy inference models. The main contribution of the article is the utilization of fuzzy logic in the adaptation of the diffusion parameter in a dynamic fashion. This parameter is in charge of creating new fractal particles, and the diversity and iteration are the input information used in the fuzzy system to control the values of diffusion.
Marylu Lagunes; Oscar Castillo; Fevrier Valdez; Jose Soria; Patricia Melin. A New Approach for Dynamic Stochastic Fractal Search with Fuzzy Logic for Parameter Adaptation. Fractal and Fractional 2021, 5, 33 .
AMA StyleMarylu Lagunes, Oscar Castillo, Fevrier Valdez, Jose Soria, Patricia Melin. A New Approach for Dynamic Stochastic Fractal Search with Fuzzy Logic for Parameter Adaptation. Fractal and Fractional. 2021; 5 (2):33.
Chicago/Turabian StyleMarylu Lagunes; Oscar Castillo; Fevrier Valdez; Jose Soria; Patricia Melin. 2021. "A New Approach for Dynamic Stochastic Fractal Search with Fuzzy Logic for Parameter Adaptation." Fractal and Fractional 5, no. 2: 33.
This article develops an approach for dynamic parameter adaptation in the Stochastic Fractal Search (SFS) method, this by adding a fuzzy inference system for the dynamic adjustment of the diffusion parameter, thus generating the Stochastic Fractal Dynamic Search (SFDS) method. The SFDS implementation was carried out and tested with the optimization of CEC’ 2017 benchmark functions comparing its results with other optimization algorithms.
Marylu L. Lagunes; Oscar Castillo; Fevrier Valdez; Jose Soria. Stochastic Fractal Dynamic Search for the Optimization of CEC’2017 Benchmark Functions. Advances in Intelligent Systems and Computing 2021, 349 -357.
AMA StyleMarylu L. Lagunes, Oscar Castillo, Fevrier Valdez, Jose Soria. Stochastic Fractal Dynamic Search for the Optimization of CEC’2017 Benchmark Functions. Advances in Intelligent Systems and Computing. 2021; ():349-357.
Chicago/Turabian StyleMarylu L. Lagunes; Oscar Castillo; Fevrier Valdez; Jose Soria. 2021. "Stochastic Fractal Dynamic Search for the Optimization of CEC’2017 Benchmark Functions." Advances in Intelligent Systems and Computing , no. : 349-357.