CMACGSA: Improved Gravitational Search Algorithm Based on Cerebellar Model Articulation Controller for Optimization by Nazmiye Ebru Bulut, Emre Dandil, Ugur Yuzgec, Alpaslan Duysak

“…Recent advances in the field often involve hybrid methods that combine several algorithms to improve performance. This study introduces an improved Gravitational Search Algorithm, named CMACGSA, which incorporates the Cerebellar Model Articulation Controller (CMAC)-a neural network model-to enhance the performance of Gravitational Search Algorithm (GSA). …”
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Optimization Performance and Efficiency Improvement of Microgrid Scheduling Model by Honggang JIA, Zhuding WANG, Yuanyuan YUE, Huan YAN, Na YAN, Qiangfei CAO

“…First of all, considering the cost of electricity charges, the cost of energy storage regulation, the user’s inappropriate cost and the benefit of response subsidies, an optimization model with the goal of minimizing the daily comprehensive power consumption cost is established; Then, aiming at the problem that the global optimization ability of the standard differential evolution algorithm is insufficient and the solution efficiency needs to be improved, the scaling factor and crossover operator are optimized and improved to form an adaptive hybrid differential evolution algorithm; Finally, taking the micro grid system as an example, the operation optimization of energy storage and demand response and the comparative analysis of calculation examples are carried out.The results show that the proposed method is suitable for multi scenario computing and has high optimization performance and solving efficiency.…”
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Improving Performance of the Convolutional Neural Networks for Electricity Theft Detection by using Cheetah Optimization Algorithm by Hassan Ghaedi, Seyed Reza Kamel Tabbakh, Reza Ghaemi

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A Model Predictive Control to Improve Grid Resilience by Joseph Young, David G. Wilson, Wayne Weaver, Rush D. Robinett

“…The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. …”
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Application of improved GA in optimizing rural tourism routes by Yin Longjie, Li Muzi

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Parameter Sensitivity Analysis and Algorithm Improvement of Optimization Scheduling Model for Cascade Pumping Stations by LIU Xiaolian, LI Zhenrong, WANG Xue-ni, ZHAI Yu, ZHANG Lei-ke, GUO Weiwei, TIAN Yu

“…ObjectiveThe low operating efficiency, massive energy consumption and large carbon emissions often exist in the operation of cascade pumping stations. To improve the operational efficiency of cascade pumping stations and vigorously promote dual carbon construction, an optimization scheduling model for cascade pumping stations was established with the goal of minimizing carbon emissions, and the Runge Kutta algorithm (RUN) was introduced to solve the model. …”
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Construction of Orchard Agricultural Machinery Dispatching Model Based on Improved Beetle Optimization Algorithm by Lixing Liu, Hongjie Liu, Jianping Li, Pengfei Wang, Xin Yang

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An Adaptive Fusion Path Tracking Strategy for Autonomous Vehicles Based on Improved ACO Algorithm by Jihan Zhang, Yuan Wang, Jinyan Hu, Hongwu You

“…Although methods based on dynamic models and optimization theory can improve tracking performance, most autonomous systems lack high-fidelity models and the complexity of optimization processes lead to increase computational burden. …”
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IGWO-MSVR model for predicting stress in coal seam during drilling process by Jian Tan, Yanfeng Geng, Liangke Xu

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Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

“…For the prediction of VIV parameters, the Random Forest model is the most effective. The RMSE values of the improved optimal algorithm are 0.017, 0.026, and 0.295, and the R² values are 0.9421, 0.8875, and 0.9462. …”
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An improvement in the design process of sustainable peak power rating transformer for solar utility by Emir Yükselen, Ebrahim Rahimpour

“…Such upgrades are essential for transitioning to a zero-emission electricity system and developing green energy projects.In this paper, a transformer has been studied using a combination of electrical design and 3D finite element method simulation to evaluate various design parameters. An optimization study has been conducted using an innovative multi-objective genetic algorithm utilizing a cost function that factors in size and material costs to identify the most efficient and cost-effective design solutions.The proposed design method was then validated through thermal model simulations and experimental tests based on the photovoltaic load cycle. …”
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Retracted: Optimization Calculation Method and Mathematical Modeling of Big Data Chaotic Model Based on Improved Genetic Algorithm by Journal of Function Spaces

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Designing a new optimal controller for a PEMFC by an improved design of the Coot Optimizer by Zheng Wang, Mehrdad Rezaie, Gholamreza Fathi

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Prediction of Earthquake Death Toll Based on Principal Component Analysis, Improved Whale Optimization Algorithm, and Extreme Gradient Boosting by Chenhui Wang, Xiaotao Zhang, Xiaoshan Wang, Guoping Chang

“…To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). …”
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Improved Sparrow Search Algorithm for Sparse Array Optimization by Juanjuan Ji, Jie Su, Lanfang Zhang, Liuying Zhang, Julang Jiang, Hongliang Ma

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Impact of an improved random forest-based financial management model on the effectiveness of corporate sustainability decisions by Jianhui Zhang

“…In order to improve the generalization ability of financial management models, pruning methods were adopted in the study to avoid overfitting. …”
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Improving Quantum Optimization Algorithms by Constraint Relaxation by Tomasz Pecyna, Rafał Różycki

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Tuning Genetic Algorithm Parameters to Improve Convergence Time by Maria Angelova, Tania Pencheva

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Improving the Solving of Optimization Problems: A Comprehensive Review of Quantum Approaches by Deborah Volpe, Giacomo Orlandi, Giovanna Turvani

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Data Decomposition Modeling Based on Improved Dung Beetle Optimization Algorithm for Wind Power Prediction by Jiajian Ke, Tian Chen

“…To enhance prediction accuracy, this paper presents a hybrid wind power prediction model that integrates the improved complementary ensemble empirical mode decomposition (ICEEMDAN), the RIME optimization algorithm (RIME), sample entropy (SE), the improved dung beetle optimization (IDBO) algorithm, the bidirectional long short-term memory (BiLSTM) network, and multi-head attention (MHA). …”
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