Exploration and comparison of the effectiveness of swarm intelligence algorithm in early identification of cardiovascular disease by Tiantian Bai, Mengru Xu, Taotao Zhang, Xianjie Jia, Fuzhi Wang, Xiuling Jiang, Xing Wei

“…This study focuses on integrating swarm intelligence feature selection algorithms (including whale optimization algorithm, cuckoo search algorithm, flower pollination algorithm, Harris hawk optimization algorithm, particle swarm optimization algorithm, and genetic algorithm) with machine learning technology to improve the early diagnosis of cardiovascular disease. …”
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Co-Optimization Operation of Distribution Network-Containing Shared Energy Storage Multi-Microgrids Based on Multi-Body Game by Hao Wu, Ge Cao, Rong Jia, Yan Liang

“…The model is solved based on an outer-layer genetic algorithm nested with an inner-layer solver to determine the electricity purchase and sale prices among the distribution network, multi-microgrids, and shared energy storage at various time periods, thereby minimizing operational costs. …”
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An Improved Topology of Isolated Bidirectional Resonant DC-DC Converter Based on Wide Bandgap Transistors for Electric Vehicle Onboard Chargers by Md. Tanvir Shahed, A. B. M. Harun-Ur Rashid

“…The PID controller parameters have been optimized using both the genetic algorithm (GA) and particle swarm optimization (PSO) algorithm and a comparative analysis has been presented between the two algorithms. …”
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Prediction of the cutting tool wear during dry hard turning of AISI D2 steel by using models based on Learning process and GA polyfit by Khaled Djellouli, Kamel Haddouche, Mostefa Belarbi, Zoubir Aich

“…For this purpose, the current research focuses on the development of predictive models of flank wear based on Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Machine (SVM), and Polynomial Fit using Genetic Algorithm (GAPOLYFITN). The simulation process involves considering input variables including feed (f), cutting speed (Vc), and cutting time (tc); the output is the flank wear (VB). …”
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Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques by Sylvester M. Sefa-Yeboah, Kwabena Osei Annor, Valencia J. Koomson, Firibu K. Saalia, Matilda Steiner-Asiedu, Godfrey A. Mills

“…In this work, we present an artificial intelligence- (AI-) based application that is driven by a genetic algorithm (GA) as a potential tool for tracking a user’s energy balance and predicting possible calorie intake required to meet daily calorie needs for obesity management. …”
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Mathematical modelling and optimization of cutting conditions in turning operation on MDN 350 steel with carbide inserts by Syed Adil, A. Krishnaiah, D. Srinivas Rao

“…Artificial neural networks technique, which is well known for its versatility to model linear as well as non-linear data, is used to express the surface roughness as a function of tool geometrical variables. Genetic Algorithm, which is an advanced optimization technique known for its intricate search for optimal solutions, is used for optimizing surface roughness with optimal combination of the geometrical parameters. …”
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An Energy-Balanced Path Planning Algorithm for Multiple Ferrying UAVs Based on GA by Lisong Wang, Xiaoliang Zhang, Pingyu Deng, Jiexiang Kang, Zhongjie Gao, Liang Liu

“…Further, we model the energy-balanced path-planning problem for multiple ferrying UAVs, which actually is a multiobject optimization problem of minimizing the planned path length and minimizing the variance of all ferrying UAVs’ energy-factor. Based on the genetic algorithm, we design and implement an energy-balanced path planning algorithm (EMTSPA) for multiple ferrying UAVs to solve this multiobject optimization problem. …”
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Optimization of a photovoltaic/wind/battery energy-based microgrid in distribution network using machine learning and fuzzy multi-objective improved Kepler optimizer algorithms by Fude Duan, Mahdiyeh Eslami, Mohammad Khajehzadeh, Ali Basem, Dheyaa J. Jasim, Sivaprakasam Palani

“…Also, the MOIKOA superior capability is validated in comparison with the multi-objective conventional Kepler optimization algorithm, multi-objective particle swarm optimization, and multi-objective genetic algorithm in problem-solving. The findings are cleared that microgrid multi-objective optimization in the distribution network considering forecasted data based on the MLP-ANN causes an increase of 3.50%, 2.33%, and 1.98%, respectively, in annual energy losses, voltage deviation, and the purchased power cost from the HMG compared to the real data-based optimization. …”
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Patch-Level and Neighborhood-Dependency Spatial Optimization Method (PNO): Application to Urban Land-Use Planning to Facilitate Both Socio-Economic and Environmental Development in... by Yuhan Cheng, Xiuyuan Zhang, Qi Zhou, Xiaoyan Dong, Shihong Du

“…The PNO represents land-use patterns in a graph structure, quantifies land-use patterns’ impacts on the population, economy, and land surface temperature, defines the spatiotemporal constraints of land-use optimization considering neighborhood-dependency and optimization sequences, and finally optimizes land uses and their spatial layouts based on a multi-objective genetic algorithm. Experiments were conducted in the urban area of Beijing, and the results suggested that, after optimization, the population and GDP can be improved by 667,323 people (4.72%) and USD 10.69 billion in products (2.75%) in the study area; meanwhile, the land surface temperature can be reduced by 0.12 °C (−0.32%). …”
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Machine learning assisted prediction with data driven robust optimization: Machining process modeling of hard part turning of DC53 for tooling applications supporting semiconductor... by Mehdi Tlija, Muhammad Sana, Anamta Khan, Sana Hassan, Muhammad Umar Farooq

“…The optimized architectures are used as prediction models to a non-sorting genetic algorithm (NSGA-II) to determine the optimal compromise among all conflicting responses. …”
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Management of Uncertainty by Statistical Process Control and a Genetic Tuned Fuzzy System by Stephan Birle, Mohamed Ahmed Hussein, Thomas Becker

“…Additionally, in order to stay within the process corridors, a genetic algorithm was applied to tune the input and output fuzzy sets of a preliminarily parameterized fuzzy controller. …”
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Spatiotemporal Evolution Characteristics of Fluid Flow through Large-Scale 3D Rock Mass Containing Filling Joints: An Experimental and Numerical Study by Qian Yin, Hongwen Jing, Tantan Zhu, Lizhou Wu, Haijian Su, Liyuan Yu

“…The water pressure contour planes distributed along the flowing path generally transfer from a “long funnel” shape to a “short funnel” shape before reaching a series of parallel pressure planes perpendicular to the joint direction. By using the genetic algorithm, the coupling influences of these factors on the pore water pressure and flow velocity were investigated, and the decision parameters were optimized. …”
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Study on Intelligent Classing of Public Welfare Forestland in Kunyu City by Meng Sha, Hua Yang, Jianwei Wu, Jianning Qi

“…Unlike previous approaches, the SVM model is optimized with Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) to automatically determine classification parameters, overcoming the limitations of manual rule-based methods. …”
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Sustainable synthesis and advanced optimization of Prosopis juliflora biomass catalyst for efficient biodiesel production and environmental impact assessment by Thota S S Bhaskara Rao, Manikandaraja Gnanaprakasam, Rajayokkiam Manimaran, Dhinesh Balasubramanian, Utku Kale, Artūras Kilikevičius

“…Abstract The present research focuses on developing an innovative biochar-based heterogeneous catalyst from Prosopis Juliflora biomass waste using response surface methodology and genetic algorithm (GA) to optimize pyrolysis parameters, achieving a 46.31% PJBC yield from 60 mg of biomass at 790 °C for 60 min. …”
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Sustainability metrics targeted optimization and electric discharge process modelling by neural networks by Muhammad Sana, Muhammad Asad, Muhammad Umar Farooq, Mehdi Tlija, Rodolfo Haber

“…Moreover, multi-response optimization through the non-dominated sorting genetic algorithm (NSGA-II) has also been performed. The magnitudes of MRRCT, SRCT, and SECCT obtained by multi-response optimization are 64.82%, 27.45%, and 46.60% are better than the values obtained by un-optimized settings of CT brass electrodes. …”
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Integration of artificial intelligence and advanced optimization techniques for continuous gas lift under restricted gas supply: A case study by Leila Zeinolabedini, Forough Ameli, Abdolhossein Hemmati-Sarapardeh

“…To optimize the selected input variables, including tubing inside diameter, gas injection rate, and separator pressure, various optimization algorithms such as particle swarm optimization (PSO), ant colony optimization (ACO), genetic algorithm (GA), and a Novel optimization algorithm in a gas-lift study called grey wolf optimization (GWO), were utilized considering the constraint of the limited available gas. …”
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Energy-Saving Metro Train Timetable Optimization Method Based on a Dynamic Passenger Flow Distribution by Jingshuang Li, Fuquan Pan, Hailiang Tang, Sen Tong, Lixia Zhang, Xinguang Li, Xiaoxia Yang

“…A particle swarm optimization and genetic algorithm (PSO-GA) structure is designed to solve the model. …”
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Advancing Horticultural Crop Loss Reduction Through Robotic and AI Technologies: Innovations, Applications, and Practical Implications by H. W. Gammanpila, M. A. Nethmini Sashika, S. V. G. N. Priyadarshani

“…Tobal and Mokthar in 2014 pioneered an AI-assisted image processing method for weed identification, introducing an evolutionary ANN to optimize neural parameters using a genetic algorithm. However, the implementation of these technologies face challenges such as high initial costs, the need for technical expertise, and the integration of various data sources. …”
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Genetic Fuzzy System untuk Klasifikasi Tutupan Lahan Berdasarkan Foto Udara Unmanned Aerial Vehicle (UAV) by Budi Darma Setiawan, Alfi Nur Rusydi

“…The genetic fuzzy system is a classification method using a fuzzy system whose membership function is optimized using a genetic algorithm. The process consists of two stages, namely the training process, to find good fuzzy rules, and then proceed with tuning processes, namely the process of shifting the value constraints on the membership function of the fuzzy set used. …”
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Research on leakage and diffusion behavior of hydrogen doped natural gas in integrated pipeline corridors based on data drive by Xiaolong Gong, Hua Li, Cheng Li, Mingyue Kou, Lingxu Kong, Hongcheng Liu

“…In addition, the backpropagation neural network (BPNN) combined with the global optimization capability of genetic algorithm and the nonlinear mapping capability of neural network is used in this paper to provide a reliable technical means for the accurate prediction of explosion risk volume, which has important application value in the safety design of pipeline corridor and accident prevention and control. …”
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