Research on wheelchair form design based on Kansei engineering and GWO-BP neural network by Weilin Cai, Zhengyu Wang, Yi Wang, Meiyu Zhou

“…This study proposes a wheelchair form design method based on the Kansei engineering approach, which integrates the evaluation grid method (EGM), grey wolf optimization (GWO) algorithm, and back propagation neural network (BPNN) technology. …”
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Methodology for the development of identification criteria of stone fruit brandy by L. N. Krikunova, S. M. Tomgorova, V. A. Zaharova

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Ethical theories, governance models, and strategic frameworks for responsible AI adoption and organizational success by Mitra Madanchian, Hamed Taherdoost, Hamed Taherdoost

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Study on the calculation of surface residual deformation in goaf based on the Gudermann time function by Haiguang Du, Wenchang Wang, Zhilin Dun, Lianwei Ren, Yakun Nan

“…In order to comprehensively and effectively grasp the dynamic evolution process of surface movement and deformation, and realize the scientific and accurate residual deformation calculation of each key point of the surface in goaf, the Gudermann time function for dynamic anticipation is established by introducing the Gudermann function and optimizing it, the spatial and temporal characteristics of this function in the subsidence prediction are analyzed, and the influence law of parameter changes on the surface subsidence, subsidence velocity and subsidence acceleration curve patterns of the Gudermann time function is discussed, and the method of extracting the optimal values of the function parameters by Simulated Annealing Algorithm (SAA) is presented. …”
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The accuracy of an electronic-Surprise-Question defining end-of-life cohorts in a whole adult population by algorithmic digital risk stratification: the Proactive Risk-Based and Da... by Baldev M. Singh, Nisha Kumari-Dewat, Vijay Klaire, Jonathan Lampitt, Amy Palmer, Adam Ryder, Kamran Ahmed, Mona Sidhu, Hannah Jennens, Ananth Viswanath, Emma Parry

“…This was triaged in a 2-step algorithm, based on care process measures and probability cut points. …”
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Sowing Depth Monitoring System for High-Speed Precision Planters Based on Multi-Sensor Data Fusion by Song Wang, Shujuan Yi, Bin Zhao, Yifei Li, Shuaifei Li, Guixiang Tao, Xin Mao, Wensheng Sun

“…Finally, a multi-sensor data fusion algorithm for optimising four key parameters in the extended Kalman filter (EKF) using an improved sparrow search algorithm (ISSA) is proposed. …”
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Construction of application platform for operational data of natural gas pipeline network by Hongtao DIAO, Weichao YU, Kaihong WANG, Huai SU, Yi ZHANG, Zhaoming YANG

“…Further research and development efforts led to the creation of data exchange technology with unified lower features, aimed at exploring the value of operational data within its network, optimizing the data structure, and integrating data assets. …”
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Seasonally Adaptive VMD-SSA-LSTM: A Hybrid Deep Learning Framework for High-Accuracy District Heating Load Forecasting by Yu Zhang, Keyong Hu, Lei Lu, Qingqing Yang, Min Fang

“…The model establishes a dynamically adaptive forecasting framework through synergistic integration of the Sparrow Search Algorithm (SSA), Variational Mode Decomposition (VMD), and Long Short-Term Memory (LSTM) network. …”
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Minimization of total costs for distribution systems with battery energy storage systems and renewable energy sources by Thai Dinh Pham, Thang Trung Nguyen, Le Chi Kien

“…The proposed solution by MCOA has demonstrated superiority over other methods through total cost savings of up to 24.13% and 27.46% in IEEE 123-bus UDS and 55-bus BDS, while the values are only 23.11% and 26.50% for salp swarm algorithm (SSA) and 23.76% and 26.78% for coyote optimization algorithm (COA), respectively, as compared to the original cases. …”
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Optimizing oil production forecasts in Iranian oil fields: a comprehensive analysis using ensemble learning techniques by Mohammad Ghodsi, Pouya Vaziri, Mahdi Kanaani, Behnam Sedaee

“…Unlike traditional forecasting methods, which often rely on single-model approaches with limited adaptability to complex, the methodology integrates multiple machine learning algorithms each optimized using distinct, hyperparameter tuning techniques. …”
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A spatio-temporal fusion-based approach for multi-dimensional classification of Parkinson’s disease progression using multi-modal dataset by Vinay Kukreja, Vandana Ahuja, Modafar Ati, Hariharan Shanmugasundaram, Murugaperumal Krishnamoorthy, Rishabh Sharma, Abhishek Bhattacherjee

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Adaptive Multi-Objective Firefly Optimization for Energy-Efficient and QoS-Aware Scheduling in Distributed Green Data Centers by Ahmed Chiheb Ammari, Wael Labidi, Rami Al-Hmouz

“…AFBO is evaluated using real-world trace-driven simulations and compared against benchmark multi-objective algorithms, including multi-objective particle swarm optimization (MOPSO), simulated annealing-based bi-objective differential evolution (SBDE), and the baseline Multi-Objective Firefly Algorithm (MOFA). …”
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Synergistic Hierarchical Bi-Level Optimization of Demand Response Programs and Smart Inverter Volt/Var Control for Maximizing Hosting Capacity of Power Systems With Renewable-Based... by Zenhom M. Zenhom, Shady H. E. Abdel Aleem, Essam Aboul Zahab, Ziad M. Ali, Abdulaziz Almalaq, Tarek A. Boghdady

“…Renewable-based distributed generation (DG) offers economic and environmental benefits, but integrating it into the distribution network (DN) poses technical challenges. …”
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Artificial intelligence-optimized shield parameters for soft ground tunneling in urban environment: A case study of Bangkok MRT Blue Line by Sahatsawat Wainiphithapong, Chana Phutthananon, Sompote Youwai, Pitthaya Jamsawang, Phattarawan Malaisree, Ochok Duangsano, Pornkasem Jongpradist

“…This integrated framework, which combines the non-dominated sorting genetic algorithm (NSGA-II) with LSTM neural networks, is applied to MOO to identify the optimal SOPs, while accounting for their influence on S variation as a time-series over 11 timesteps, as considered in this study. …”
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ПРОЕКТ “ARIA”: ШЛЯХИ НАДАННЯ МЕДИЧНОЇ ДОПОМОГИ ПРИ АЛЕРГІЧНОМУ РИНІТІ (2019 РІК) – УКРАЇНА by І. Гогунська, Д. Заболотна, С. Зайков, И. Кайдашев, Т. Уманець, В. Чоп’як, Л. Яшина, С. Бахерт, П.В. Хеллінгс, О. Пфаар, Х.Дж. Шунеманн, Д. Воллес, А. Бедбрук, В. Чарлевськи, Ж. Буске

“…The evaluation of real-life Integrated Care Pathways (ICPs) was recommended fordigitally-enabled, integrated, person-centred care for rhinitis and asthma multimorbidity embedding environmental exposure. …”
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Inconsistency evaluation of the curriculum logical structure by Yu. D. Ageev, S. V. Fedoseev, Yu. A. Kavin, S. G. Vorona, I. S. Pavlovskiy

“…Three models of curriculum structure are developed:Elementary model of interdisciplinary communication;Curriculum network model;Hierarchical curriculum model.Based on the parameters of the hierarchical curriculum model, using three adapted algorithms, the value of the inconsistency index of the curriculum structure in the direction of preparation “Applied Informatics” is calculated. …”
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A Summary of Recent Advances in the Literature on Machine Learning Techniques for Remote Sensing of Groundwater Dependent Ecosystems (GDEs) from Space by Chantel Nthabiseng Chiloane, Timothy Dube, Mbulisi Sibanda, Tatenda Dalu, Cletah Shoko

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Multi-Parameter Optimization of Angle Transmission Ratio of Steer-by-Wire Vehicle by Wenguang Liu, Suo Liu, Huajun Che, Xi Liu, Hua Ding

“…The new control strategy uses a genetic algorithm to optimize the yaw rate and lateral acceleration gain values at different speeds, and the two are weighted. …”
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Enhancing root-zone soil moisture estimation using Richards' equation and dynamic surface soil moisture data by Xizhuoma Zha, Wenbin Zhu, Yan Han, Aifeng Lv

“…The SSMRE model exhibits R values of 0.9, 0.85, 0.74, and 0.72, with RMSE values of 0.04, 0.02, 0.04, and 0.05. …”
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Performance Improvement in a Vehicle Suspension System with FLQG and LQG Control Methods by Tayfun Abut, Enver Salkım, Andreas Demosthenous

“…The linear quadratic Gaussian (LQG) and fuzzy linear quadratic Gaussian (FLQG) control methods were designed and used for active control to increase vehicle handling and passenger comfort, with the aim of reducing or eliminating vibrations by performing active control of passive suspension systems using these methods. The optimum values of the coefficients of the points where the membership functions of the LQG and Fuzzy LQG methods touch were obtained using the grey wolf optimization (GWO) algorithm. …”
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