Rainfall Forecasting Using a BiLSTM Model Optimized by an Improved Whale Migration Algorithm and Variational Mode Decomposition by Yueqiao Yang, Shichuang Li, Ting Zhou, Liang Zhao, Xiao Shi, Boni Du

“…Secondly, IWMA is utilized to globally optimize multiple hyperparameters of the BiLSTM model, enhancing its ability to capture complex nonlinear relationships and long-term dependencies. …”
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Primary Frequency Regulation Modeling of Deep Peak Regulation Unit Based on Improved Group Optimization Algorithm by Guoqiang YU, Xiaobo CUI, Yiyue SHI, Keyi TANG, Tianhai ZHANG

“…Then the unknown parameter values in the model are derived by using an improved group optimization algorithm with better global search capability. …”
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Retracted: Modeling and Simulation of English Speech Rationality Optimization Recognition Based on Improved Particle Filter Algorithm by null Complexity

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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Muhammad Shafiqul Islam, Mohd Ashraf Ahmad

“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Research on manufacturing quality improvement based on product gene evaluation method and a meta-heuristic algorithm with hybrid encoding scheme by Wenxiang Xu, Chao Wang, Shimin Xu, Junyong Liang, Dezheng Liu, Baigang Du

“…In this method, an optimization model is established and described by formulas, in which three optimization objectives including production quality, costs, and time are involved. …”
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A Feasibility Study of a Virtual Power Line Device to Improve Hosting Capacity in Renewable Energy Sources by Seong-Eun Rho, Sung-Moon Choi, Joong-Seon Lee, Hyun-Sang You, Seung-Ho Lee, Dae-Seok Rho

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Parameter Optimization of MALDI-TOF MS Based on Improved Whale Optimization Algorithm by Yu-peng ZHANG, Yu-gong DANG, Hui-yuan YANG, Zhi-gang ZHOU, Gao-hang JIANG

“…To address the shortcomings of the Whale optimization algorithm, including slow convergence speed, low precision and susceptibility to local optima, improvements were made on the convergence factor, inertia weight and position update strategy. …”
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PREDICTION OF TBM OIL TEMPERATURE BY IMPROVED CAMEL ALGORITHM ASSISTED RANDOM FOREST MODEL (MT) by REN JianJi, ZHAO RunQiu, WANG ZhenXi, LIU YuMing, YUAN YongLiang

“…Secondly, the improved camel algorithm was used to optimize the parameters of the TBM oil temperature prediction model established by the random forest to obtain the best model. …”
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Research on a Particle Filtering Multi-Target Tracking Algorithm for Distributed Systems by Bing Han, Zilong Ge, Zhigang Su, Jingtang Hao

“…Comparative evaluations across motion models, noise levels, and the number of targets demonstrate the outperforming performance of the proposed method compared to conventional particle filtering and the unscented Kalman filtering algorithm, with more than 7% accuracy improvement over baselines. …”
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ONBOARD FUEL PUMP FAULT DIAGNOSIS BASED ON IMPROVED SUPPORT VECTOR MACHINE AND EXPERIMENTAL RESEARCH by LIANG Wei, JING Bo, JIAO XiaoXuan, QIANG XiaoQing, LIU XiaoDong

“…Meanwhile,the fault feature vectors are used to train and validate this classification model. The experimental results show that this method not only can improve the classification accuracy on fault diagnosis,but also can optimize the use of sensors by using only one vibration sensor and one pressure sensor to recognize the fault signals.…”
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The algorithm for applying the process maturity model to improve business processes in organization by S. I. Artemyeva, G. S. Kublashvili, A. G. Zaitsev

“…The article considers the most popular maturity models. An algorithm for applying these models is developed. …”
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Smart homes energy management: Optimal multi-objective appliance scheduling model considering electrical energy storage and renewable energy resources by Moslem Dehghani, Seyyed Mohammad Bornapour

“…Also, in the proposed mathematical formulation, the bought and selling energy is considered during the day. An improved Biogeography-based optimization algorithm (IBBO) is used to solve the multi-objective problem. …”
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A new approach for bin packing problem using knowledge reuse and improved heuristic by Jie Fang, Xubing Chen, Yunqing Rao, Yili Peng, kuan Yan

“…The classic packing solution is a hybrid algorithm based on heuristic positioning and meta-heuristic sequencing, which has the problems of complex solving rules and high time cost. …”
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Real-Time Optimal Control Strategy for Multienergy Complementary Microgrid System Based on Double-Layer Nondominated Sorting Genetic Algorithm by Min Mou, Yuhao Zhou, Wenguang Zheng, Zhongping Zhang, Da Lin, Dongdong Ke

“…In this paper, a typical model of energy input-output is established. This model combines with the operation control strategy suitable for multienergy complementary microgrid system, considers the operation mode and equipment characteristics of the system, and uses a double-layer nondominated sorting genetic algorithm to optimize the operation of each equipment in the multienergy complementary system in real time, so as to reduce the operation cost of the system.…”
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Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

“…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
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Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance by Sugunakar Mamidala, Yellapragada Venkata Pavan Kumar, Rammohan Mallipeddi

“…This paper proposes a novel framework that integrates deep Q networks (DQNs) for real-time charging optimization, coupled with multimodal bioinspired algorithms like ant lion optimization (ALO) and moth flame optimization (MFO). …”
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Adaptive Grasp Pose Optimization for Robotic Arms Using Low-Cost Depth Sensors in Complex Environments by Aiguo Chen, Xuanfeng Li, Kerui Cen, Chitin Hon

“…Unlike traditional deep learning methods, which suffer from high data dependency and inefficiency with low-precision point clouds, the proposed approach uses ellipsoidal modeling to overcome these issues. The algorithm segments the target and then applies a three-stage optimization to refine the grasping path. …”
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Volt/VAr Regulation of the West Mediterranean Regional Electrical Grids Using SVC/STATCOM Devices With Neural Network Algorithms by H. Feza Carlak, Ergin Kayar

“…A load flow and short circuit analysis is performed on the designed transmission system for a number of critical scenarios. The modeled power system is optimized for the size and location of the FACTS devices by applying genetic algorithms (GAs) and particle swarm optimization (PSO) algorithms to the selected busbars of the FACTS devices, a strategy designed to significantly reduce system losses. …”
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Optimal Computation Offloading Decisions Based on System Utility and Cost Balance by Bingxue Zhang, Xisheng Li, Jia You

“…By calculating the full load rate of edge server clusters, we describe and evaluate the operational efficiency of the system, aiming to design a computation offloading decision scheme that not only reduces costs, but also enhances system utility. Based on the new evaluation model, an objective function is constructed to minimize the system’s cost-utility ratio, and an improved particle swarm optimization algorithm with enhanced search capabilities is proposed to solve it by designing a computation offloading strategy. …”
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Surfactants Adsorption onto Algerian Rock Reservoir for Enhanced Oil Recovery Applications: Prediction and Optimization Using Design of Experiments, Artificial Neural Networks, and... by Kahina Imene Benramdane, Mohamed El Moundhir Hadji, Mohamed Khodja, Nadjib Drouiche, Bruno Grassl, Seif El Islam Lebouachera

“…Unlike traditional data acquisition methods, this approach enables a methodical and structured exploration of adsorption behavior while reducing the number of required experiments, leading to improved prediction accuracy, optimization, and cost-effectiveness. …”
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