This research was conducted with the objective of identifying and ranking the tourism sector development strategies for the Changbai Mountain. The SWOT approach was used to construct strategies and the QSPM matrix and AHP method were employed to rank selected strategies. A questionnaire and the Delphi technique were used to collect and analyze research data from forty specialists. The effectiveness of 16 internal factors and 12 external factors in the business region was assessed. According to the results obtained, “Existence of beautiful natural features with distinctive scenery” is the most significant strength of Changbai Mountain. Also, “Inadequate amenities and weakness of infrastructure construction” has been established as the most significant weakness. The term “Adapting the development of the region to the national strategy” is among the most significant external opportunities. Additionally, the “islanding phenomenon” is one of the most significant threats. Sixteen plans were recommended for the growth of the Changbai Mountain’s tourism business. On the basis of the matrix of internal–external components in the SWOT model, an offensive strategy was identified as the optimal approach. We used the combined SWOT-AHP model with 4 criteria and 28 sub-criteria to determine the optimum strategy in the second model, and offensive methods were given the highest priority. The results showed that the “Taking advantage of the natural, historical potentials, etc.” and “Establishing an appropriate mechanism for public and private sector investment” strategies are the most crucial for improving the condition in Changbai Mountain. Therefore, special consideration should be given to the tourism potential in this region, and it should be placed on the agenda of managers and planners in order to strengthen the tourism industry, the region’s economic status, and create employment opportunities.

Using SWOT and TOPSIS models, this study aimed to determine West Lake’s potential as a tourist destination. In terms of study methodology, the current research is a descriptive survey. The TOPSIS method was used to rank strengths, weaknesses, threats, opportunities, and preferred strategies after the SWOT analysis was completed. Using a questionnaire and the Delphi method, 30 regional specialists provided research data which was collected and analyzed. Thirteen internal elements and twelve external factors affecting the West Lake tourism were identified and evaluated. Additionally, fifteen strategies were presented to improve the lake’s tourism. On the basis of the matrix of internal–external components in the SWOT model, an aggressive approach was determined to be the optimal strategic stance for West Lake. The results of the TOPSIS technique also revealed that internal strengths have a bigger impact than other elements; hence, aggressive strategies are emphasized for the growth of ecotourism in this region. Based on the results of the TOPSIS technique, the “optimal utilization of the lake’s natural, cultural, and historical potential and attractions in order to develop and attract tourists and generate jobs and revenues“ and “formulation of strategic plans to maximize potential and opportunities in order to attract tourists in all seasons of the year“ strategies were identified as the most important strategies for enhancing the West Lake tourism scenario. Therefore, it is hoped that the relevant authorities would contribute to the expansion and enhancement of the region’s economy through a focus on the vision and goals of the tourist sector and careful foresight in the implementation of these projects.

The air kerma is a key parameter in medical diagnostic radiology. Radiologists use the air kerma parameter to evaluate organ doses and any associated patient hazards. The air kerma can be simply described as the deposited kinetic energy once a photon passes through the air, and it represents the intensity of the radiation beam. Due to the heel effect in the X-ray sources of medical imaging systems, the air kerma is not uniform within the X-ray beam’s field of view. Additionally, the X-ray tube voltage can also affect this nonuniformity. In this investigation, an intelligent technique based on the radial basis function neural network (RBFNN) is presented to predict the air kerma at every point within the fields of view of the X-ray beams of medical diagnostic imaging systems based on discrete and limited measured data. First, a diagnostic imaging system was modeled with the help of the Monte Carlo N Particle X version (MCNPX) code. It should be noted that a tungsten target and beryllium window with a thickness of 1 mm (no extra filter was applied) were used for modeling the X-ray tube. Second, the air kerma was calculated at various discrete positions within the conical X-ray beam for tube voltages of 40 kV, 60 kV, 80 kV, 100 kV, 120 kV, and 140 kV (this range covers most medical X-ray imaging applications) to provide the adequate dataset for training the network. The X-ray tube voltage and location of each point at which the air kerma was calculated were used as the RBFNN inputs. The calculated air kerma was also assigned as the output. The trained RBFNN model was capable of estimating the air kerma at any random position within the X-ray beam’s field of view for X-ray tube voltages within the range of medical diagnostic radiology (20–140 kV).