An Improved Substation Locating and Sizing Method Based on the Weighted Voronoi Diagram and the Transportation Model by Shiju Wang, Zhiying Lu, Shaoyun Ge, Chengshan Wang

“…Substation locating and sizing is an important component of urban power networks. In this paper, an improved method based on the weighted Voronoi diagram and transportation model for substation planning is proposed, which can optimize the location, capacity, and power supply range for each substation with the minimum investment which contains the cost of the lines, substations, and annual operation expense. …”
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An integrated vehicle routing model to optimize agricultural products distribution in retail chains by W. Madushan Fernando, Amila Thibbotuwawa, H. Niles Perera, Peter Nielsen, Deniz Kenan Kilic

“…Numerical experiments showcase the efficiency of the proposed algorithm in solving real-world VRP problems. Moreover, the proposed VRP model achieves a 19% reduction in daily distribution costs, including a 24% saving in fuel costs. …”
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Research on pose estimation algorithm of non-cooperative target tracked vehicles based on PnP model by Zhigang Ren, Xinagjun Tang, Guoquan Ren, Dinghai Wu

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Model Optimization for High-Yield Biocrude in Co-Hydrothermal Liquefaction of Municipal Sludge by Botian HAO, Yunfei DIAO, Ya WEI, Donghai XU

“…After training with the Levenberg-Marquardt algorithm, the model′s R2 significantly improved to 0.9989, demonstrating the superiority of neural networks in modeling nonlinear complex systems. …”
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Unobtrusive Sleep Posture Detection Using a Smart Bed Mattress with Optimally Distributed Triaxial Accelerometer Array and Parallel Convolutional Spatiotemporal Network by Zhuofu Liu, Gaohan Li, Chuanyi Wang, Vincenzo Cascioli, Peter W. McCarthy

“…For sleep posture classification, we employ an improved density peak clustering algorithm that incorporates the K-nearest neighbor mechanism. …”
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Integration of Solar Energy into Smart Grids: A Cost-Effective Framework for Sustainable Power Management by Ali Raza Larik, Rahool Rai, Kashif Ahmed, Halar Mustafa

“…This system reduces consumer unit costs, ensures a steady electricity supply, enhances the current grid by feeding back excess power, and employs a smart algorithm to select the optimal power source from among the various options. …”
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Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users by Christopher Meaney, Xuesong Wang, Jun Guan, Therese A. Stukel

“…Hyper-parameter tuning using any HPO algorithm/sampler improved model discrimination (AUC=0.84), resulted in models with near perfect calibration, and consistently identified features predictive of high-need high-cost health care users. …”
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Crowding distance and IGD-driven grey wolf reinforcement learning approach for multi-objective agile earth observation satellite scheduling by He Wang, Weiquan Huang, Sindri Magnússon, Tony Lindgren, Chen Chen, Junyu Wu, Yanjie Song

“…This increased demand for complex and diverse imaging products requires addressing multi-objective optimization in practice. To this end, we propose a multi-objective agile Earth observation satellite scheduling problem (MOAEOSSP) model and introduce a reinforcement learning-based multi-objective grey wolf optimization (RLMOGWO) algorithm. …”
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Advanced Queueing and Location-Allocation Strategies for Sustainable Food Supply Chain by Amirmohammad Paksaz, Hanieh Zareian Beinabadi, Babak Moradi, Mobina Mousapour Mamoudan, Amir Aghsami

“…In large-scale scenarios, GOA significantly reduced processing times, ranging from 20.45 to 64.78 s. The optimization of processing facility locations within the supply chain, based on this model, led to improved balance between cost (up to $74.2 million), environmental impact (122,112 hazardous units), and waiting time (down to 11.75 h). …”
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Shared energy storage planning based on the adjustable potential of data center based on visual IOT platform by Lei Su, Wanli Feng, Haoyu Ma, Mingjiang Wei, RuoShi Gu, Ziya Chen, Junda Qin

“…Based the two-stage stochastic optimization model, a improved L-shaped algorithm is proposed to solve the planning model effectively, reducing computational complexity through problem decomposition. …”
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AI driven automation for enhancing sustainability efforts in CDP report analysis by Ramya Rangarajan, Tamilarasi Kathirvel Murugan, Logeswari Govindaraj, Venyaa Venkataraman, Krithik Shankar

“…The proposed system leverages publicly available Carbon Disclosure Project (CDP)-reported data to predict emissions and optimize resource allocation. The primary objective of this research is to develop a cost-effective, scalable solution that reduces emissions, improves operational efficiency, and ensures regulatory compliance within supply chains. …”
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Enhancing agricultural sustainability: Optimizing crop planting structures and spatial layouts within the water-land-energy-economy-environment-food nexus by Haowei Wu, Zhihui Li, Xiangzheng Deng, Zhe Zhao

“…In this framework, the NSGA-II algorithm was used to construct the multi-objective optimization model of crop planting structures with consideration of water and energy consumption, greenhouse gas (GHG) emissions, economic benefits, as well as food, land, and water security constraints, while the model for planting spatial layout optimization was established with consideration of crop suitability using the MaxEnt model and the improved Hungarian algorithm. …”
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Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema by Anwesa Mondal, Apurba Nandi, Subhasish Pramanik, Lakshmi Kanta Mondal

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Developing and Implementing an Artificial Intelligence (AI)-Driven System For Electricity Theft Detection by Nwamaka Georgenia Ezeji, Kingsley Ifeanyi Chibueze, Nnenna Harmony Nwobodo-Nzeribe

“…Methodology used are data collection, data analysis, feature selection with Chi-Square, feature transformation with Principal Component Analysis (PCA), Support Vector Machine (SVM) and model for electricity theft detection.   To achieve this, a Particle Swarm Optimization Algorithm (PSO) was applied to improve training performance of the SVM, using data of meter recharge information collected from Enugu Electricity Distribution Company (EEDC). …”
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Optimizing EV charging stations and power trading with deep learning and path optimization. by Qing Zhu

“…Path optimization, using the Dijkstra algorithm, minimized travel times for EV users by 11.4%. …”
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Path Optimization Model for Urban Transportation Networks under the Perspective of Environmental Pollution Protection by Can Liu, Zongping Li, Yueyang Li

“…Finally, the improved particle swarm optimization algorithm is used to solve the two-objective model to obtain the Pareto front solution set, that is, the path scheme under real-time traffic conditions. …”
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Modeling and optimizing the atmospheric water harvesting System: Application of PAN-PDMS polymeric membrane by Sepehr Sanaye, Pouya Rezvani Gil Kalaee, Javad Mahmoudimehr

“…This proposed water harvesting system is modeled in energy and economic aspects for the first time and is optimized in this research by applying multi-objective Genetic Algorithm (GA) technique. …”
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The Application of Artificial Intelligent Algorithms in Electric Propulsion by Tian Bin, An Bingchen, Xie Kan, Yang Sulan

“…These algorithms can not only train models based on data to optimize the performance of electric thrusters, but also analyze and solve the mathematical and physical models of plasmas within electric thrusters. …”
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Optimization and benefit evaluation model of a cloud computing-based platform for power enterprises by Xueli Yin, Xuguang Zhang, Luyao Pei, Rong Hu, Kaihui Ye, Kangkang Cai

“…The proposed model focuses on resource scheduling optimization, task load balancing, and improvements in computational efficiency. …”
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A Bi-Level Optimization Model for Flexible Capacity Allocation with Coordinated Planning and Operation by Xinyu Yin, Xiaoyan Bian, Qinran Zhu, Jinbin Zhao, Shunfu Lin, Kwok L. Lo

“…On this basis, the lower level simulates production to estimate daily operating costs. In addition, the model is solved iteratively using the nondominated sorting genetic algorithm-II (NSGA-II) and the linear programming method to obtain the Pareto solutions. …”
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