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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An Improved Phase Space Reconstruction Method-Based Hybrid Model for Chaotic Traffic Flow Prediction by Yue Hou, Da Li, Di Zhang, Zhiyuan Deng

“…The proposed PDRGA optimization algorithm is a lightweight improvement of the traditional genetic algorithm (GA) and solves the problem that the model tends to fall into a local optimum by optimizing the initial weights of CDBN. …”
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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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Robust adaptive control with dung beetle optimization algorithm and disturbance observer for load displacement tracking of shock absorber damper test bench. by Xiangfei Tao, Kailei Liu, Dong Han, Jing Yang, Hongbin Qiang

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”
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Application of Simulated Annealing Algorithm in the Construction of Online Examination System for Tax Law Courses by da Pan

“…This study proposes a simulated annealing (SA)-based optimization model for dynamically generating balanced online examinations in tax law courses. …”
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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

“…In this paper, a music-inspired metaheuristic optimization algorithm, named Harmony Search (HS), has been integrated with ARIMA in order to improve the forecasting of the COVID-19 data set. …”
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Improving Cardiovascular Disease Prediction through Stratified Machine Learning Models and Combined Datasets by Tara Yousif Mawlood, Alla Ahmad Hassan, Rebwar Khalid Muhammed, Aso M. Aladdin, Tarik A. Rashid, Bryar A. Hassan

“…Results revealed that ensemble models, particularly RF and DT, achieved optimal performance with 100% accuracy, while stratification significantly improved the outcomes of SVM, GNB, and GB. …”
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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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Research on cooperative control strategy for high efficiency and energy saving in virtually coupled train sets based on two-layer optimization by JIANG Sidun, FENG Jianghua, ZHANG Zhengfang, SHI Ke, LUO Qinyang

“…This key information serves as intermediate transfer variables within this two-layer model. The lower layer concentrates on energy-saving optimization, establishing an objective function for energy saving and utilizing a multi-objective particle swarm algorithm to optimize cruising curves. …”
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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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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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A Deep Reinforcement Learning-Driven Seagull Optimization Algorithm for Solving Multi-UAV Task Allocation Problem in Plateau Ecological Restoration by Lijing Qin, Zhao Zhou, Huan Liu, Zhengang Yan, Yongqiang Dai

“…To solve this model, a deep reinforcement learning-based seagull optimization algorithm (DRL-SOA) is proposed, which integrates deep reinforcement learning with the seagull optimization algorithm (SOA) for adaptive optimization. …”
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Trajectory Tracking in Autonomous Driving Based on Improved hp Adaptive Pseudospectral Method by Yingjie Liu, Qianqian Wang

“…At the same time, the tracking error of the lateral distance under the condition of <i>u</i> = 30 km/h is smaller than that of <i>u</i> = 90 km/h. The optimal path tracking control using the improved hp adaptive pseudospectral method has higher accuracy and better control effect compared to traditional control algorithms. …”
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FlexSim-Simulated PCB Assembly Line Optimization Using Deep Q-Network by Jinhao Du, Jabir Mumtaz, Wenxi Zhao, Jian Huang

“…The PCB assembly line model is constructed using the FlexSim simulation tool, and the optimal scheduling strategy is learned through the DQN algorithm. …”
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A new neurodynamic model with Adam optimization method for solving generalized eigenvalue problem by Ebrahim Ganjalipour, Khadijeh Nemati, Amir Hosein Refahi Sheikhani, Hashem Saberi Najafi

“…The experiments demonstrate that our algorithm using Adam optimizer, in comparison with other stochastic optimization methods like gradient descent works well in practice and improves complexity and accuracy of convergence.…”
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End-to-end throughput evaluation model and optimization method for dual-mode mesh network by SU Zhan, WEN Bo, ZHU Xiaorong

“…The proposed resource allocation algorithm improves throughput by 10% compared with traditional resource allocation algorithms. …”
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Optimizing the Joint Replenishment and Channel Coordination Problem under Supply Chain Environment Using a Simple and Effective Differential Evolution Algorithm by Lin Wang, Hui Qu, Shan Liu, Can Chen

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Fusion of Visible and Infrared Images Using a Reinforcement Learning System Based on Fuzzy Logic and Convolution Optimized with Wild Horse Algorithm by Mahvash Zarimeidani, Amir Amirabadi, Nasrin Amiri, Iman Ahanian, Siavash Es’haghi

“…This hybrid reinforcement learning system was optimized using algorithms including wild horse optimization (WHO), genetic algorithm (GA), and particle swarm optimization (PSO) to improve specific fusion metrics such as image correlation, similarity coefficient, image entropy, and signal-to-noise ratio. …”
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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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