Multidimensional water-economic-ecological joint optimization for Manas River Basin, China, using a dual-population co-evolutionary algorithm by Jian Qin, Yongpeng Tong, Muhammad Arsalan Farid, Heng Zhang, Hao Tian, Xiaolong Li, Xinlin He, Lianqing Xue, Yi Li, Yongli Gao, Guang Yang

“…Study focus: A multidimensional water-economic-ecological joint optimization model was constructed and solved using an improved hybrid algorithm combining Multi-Objective Particle Swarm Optimization and Non-dominated Sorting Genetic Algorithm II. …”
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Effective deployment strategies for optimizing area coverage in multistatic sonar detection based on Cassini oval approximation and a virtual force algorithm by Liufang Fu, Ming Zhou, Linzhou Xu, Xiaoming Dong, Zhu Kou, Chunyu Kang

“…The area coverage of multistatic sonar is a multi-objective optimization problem (MOOP) balancing maximum coverage against minimal cost. …”
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Research on the optimization model of anti-breast cancer candidate drugs based on machine learning by Zhou Dong, Hong Chen, Yuchen Yang, Hairong Hao

“…Additionally, a multi-model fusion strategy and Particle Swarm Optimization (PSO) algorithm were employed to optimize both biological activity and ADMET properties, thereby improving the prediction of Caco-2, CYP3A4, hERG, HOB, and MN properties. …”
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Explainable AI and optimized solar power generation forecasting model based on environmental conditions. by Rizk M Rizk-Allah, Lobna M Abouelmagd, Ashraf Darwish, Vaclav Snasel, Aboul Ella Hassanien

“…This paper proposes a model called X-LSTM-EO, which integrates explainable artificial intelligence (XAI), long short-term memory (LSTM), and equilibrium optimizer (EO) to reliably forecast solar power generation. …”
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Design, Modeling, and Optimization of a Nearly Constant Displacement Reducer with Completely Distributed Compliance by Yanchao Tong, Beibei Hou, Shuaishuai Lu, Pengbo Liu, Zhi Yang, Peng Yan

“…On the basis of sensitivity analysis to structure parameters, including node positions and beam parameters, the Particle Swarm Optimization (PSO) algorithm is used to optimize the displacement reduction performance. …”
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YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

“…To overcome these limitations, this paper introduces YOLOv11-GSF, a real-time strawberry ripeness detection algorithm based on YOLOv11, which incorporates several innovative features: a Ghost Convolution (GhostConv) convolution method for generating rich feature maps through lightweight linear transformations, thereby reducing computational overhead and enhancing resource utilization; a C3K2-SG module that combines self-moving point convolution (SMPConv) and convolutional gated linear units (CGLU) to better capture the local features of strawberry ripeness; and a F-PIoUv2 loss function inspired by Focaler IoU and PIoUv2, utilizing adaptive penalty factors and interval mapping to expedite model convergence and optimize ripeness classification. …”
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Application of harmony search algorithm in optimizing autoregressive integrated moving average: A study on a data set of Coronavirus Disease 2019 by Riya Karmakar, Sandip Chatterjee, Debabrata Datta, Dipankar Chakraborty

“…The accuracy of forecasting has significantly increased after optimizing the model using the proposed algorithm. Furthermore, a novel application of HS has also been discussed in this paper.…”
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BWO–ICEEMDAN–iTransformer: A Short-Term Load Forecasting Model for Power Systems with Parameter Optimization by Danqi Zheng, Jiyun Qin, Zhen Liu, Qinglei Zhang, Jianguo Duan, Ying Zhou

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Optimization of Rotary Blade Wear and Tillage Resistance Based on DEM-MBD Coupling Model by Zhiqiang Mao, Yang Zhang, Keping Zhang, Jiuxin Wang, Junqian Yang, Xiaobao Zheng, Shuaikang Chen, Zhongqing Yang, Biao Luo

“…To solve the problems of high tillage resistance and the rapid wear of the rotary blade during tillage, this study employed a coupled algorithm of the discrete element method (DEM) and multi-body dynamics (MBD) with Hertz–Mindlin with JKR particle contact theory to establish a rotary blade–sandy soil model. …”
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Enhanced OCR Recognition for Madurese Text Documents: A Genetic Algorithm Approach with Tesseract 5.5 by Muhammad Nazir Arifin, Muhammad Umar Mansyur, Ali Rahman, Nindian Puspa Dewi, Fauzan Prasetyo Eka Putra

“…Further optimization through language model selection, particularly using the Occitan (OCI) model, yielded 100% accuracy in specific test cases. …”
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Integrative electricity need prediction utilizing enhanced squeeze net and flexible Coyote optimization algorithm A combination of RCPs SSPs and socioeconomic by Bin Yang, Bin Song, Yadegar Abdi

“…The effectiveness of the compact network is increased by using the Flexible Coyote Optimization Algorithm (FCOA), which plays a vital role in optimizing parameters and accelerating convergence. …”
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Three-dimensional design, simulation and optimization of a centrifugal compressor impeller with double-splitter blades by Mohammadjavad Tasharrofi, Mojtaba Heidarian Shahri, Ali Madadi

“…Since the optimization process only using genetic algorithms is very time-consuming and has high computational costs, artificial neural networks were used to reduce costs. …”
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Estimation of Lithium-Ion Battery SOC Based on IFFRLS-IMMUKF by Xianguang Zhao, Tao Wang, Li Li, Yanqing Cheng

“…To tackle the challenge of precise SOC estimation in complex environments, this study introduces an improved forgetting factor recursive least squares (IFFRLS) method, which integrates the Golden Jackal optimization (GJO) algorithm with the traditional FFRLS method. …”
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UAVRM-A*: A Complex Network and 3D Radio Map-Based Algorithm for Optimizing Cellular-Connected UAV Path Planning by Yanming Chai, Yapeng Wang, Xu Yang, Sio-Kei Im, Qibin He

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Optimizing Outdoor Micro-Space Design for Prolonged Activity Duration: A Study Integrating Rough Set Theory and the PSO-SVR Algorithm by Jingwen Tian, Zimo Chen, Lingling Yuan, Hongtao Zhou

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Research on Operation Curve Planning Technology Adaptive to Undulating Tracks for Heavy-Haul Trains by JIANG Jie, ZHANG Zhengfang, LUO Yuan, ZHOU Huangbiao, XIONG Jiayuan

“…Finally, the ant colony algorithm was used to solve this model, resulting in the generation of the optimal control curve for heavy-haul trains running on undulating track sections. …”
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A distributional reinforcement learning model for optimal glucose control after cardiac surgery by Jacob M. Desman, Zhang-Wei Hong, Moein Sabounchi, Ashwin S. Sawant, Jaskirat Gill, Ana C. Costa, Gagan Kumar, Rajeev Sharma, Arpeta Gupta, Paul McCarthy, Veena Nandwani, Doug Powell, Alexandra Carideo, Donnie Goodwin, Sanam Ahmed, Umesh Gidwani, Matthew A. Levin, Robin Varghese, Farzan Filsoufi, Robert Freeman, Avniel Shetreat-Klein, Alexander W. Charney, Ira Hofer, Lili Chan, David Reich, Patricia Kovatch, Roopa Kohli-Seth, Monica Kraft, Pulkit Agrawal, John A. Kellum, Girish N. Nadkarni, Ankit Sakhuja

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Leveraging Game Theory to Design Incentive-Compatible Time-Varying electricity pricing with Demand-Side management by Magda I. El-Afifi, Bishoy E. Sedhom, Abdelfattah A. Eladl, Padmanaban Sanjeevikumar, Samaa Fawzy

“…This study investigates a novel approach to improve energy efficiency through a Demand Response (DR) program with a Game Theory (GT)-based Time-of-Use (ToU) pricing model. …”
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Efficient cooling capability in microchannel heat sink reinforced with Y-shaped fins: Based on artificial neural network, genetic algorithm, Pareto front, and numerical simulation by Xiang Ma, Ali Basem, Pradeep Kumar Singh, Rebwar Nasir Dara, Ahmad Almadhor, Amira K. Hajri, Raymond Ghandour, Barno Abdullaeva, H. Elhosiny Ali, Samah G. Babiker

“…A genetic algorithm was employed for single-objective optimization targeting three criteria: maximizing total efficiency, minimizing pressure drop, and maximizing the Nusselt number. …”
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Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases by A. Naderi Beni, H. Bagherpour, J. Amiri Parian

“…Today, deep convolutional neural networks (DCNNs), a novel approach to image classification, have become the most crucial detection method. DCNNs improve detection or classification accuracy by developing machine-learning models with many hidden layers to extract optimal features. …”
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