An advanced CNN-attention model with IFTTA optimization for prediction air consumption of relay nozzles by Shen Min, Shao Ning, Cao Yongbo, Xiong Xiaoshuang, Yang Xuezheng, Wang Zhen, Yu Lianqing

“…This paper proposes a Convolutional Neural Network (CNN)-Attention regression model to predict air consumption of the relay nozzle, enhancing accuracy and efficiency with an Improved Football Team Training Algorithm (IFTTA). …”
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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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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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An Improved Squirrel Search Algorithm for Optimization by Tongyi Zheng, Weili Luo

“…Squirrel search algorithm (SSA) is a new biological-inspired optimization algorithm, which has been proved to be more effective for solving unimodal, multimodal, and multidimensional optimization problems. …”
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Tuning Genetic Algorithm Parameters to Improve Convergence Time by Maria Angelova, Tania Pencheva

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Application of improved GA in optimizing rural tourism routes by Yin Longjie, Li Muzi

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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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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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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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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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Combination of Intermittent Search Strategy and an Improve Particle Swarm Optimization algorithm (IPSO) for model updating by Thanh Sang-To, Hoang-Le Minh, Tran-Thanh Danh, Samir Khatir, Magd Abdel Wahab., Thanh Cuong-Le

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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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Improving Quantum Optimization Algorithms by Constraint Relaxation by Tomasz Pecyna, Rafał Różycki

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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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A Novel Exploration Stage Approach to Improve Crayfish Optimization Algorithm: Solution to Real-World Engineering Design Problems by Harun Gezici

“…In order to compensate these shortcomings, this study proposes an Improved Crayfish Optimization Algorithm (ICOA) that designs the competition stage with three modifications: (1) adaptive step length mechanism inversely proportional to the number of iterations, which enables exploration in early iterations and exploitation in later stages, (2) vector mapping that increases stochastic behavior and improves efficiency in high-dimensional spaces, (3) removing the X_shade parameter in order to abstain from early convergence. …”
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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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An electricity price optimization model considering time-of-use and active distribution network efficiency improvements by Yan Li, Yaheng Su, Qixin Zhao, Bala Wuda, Kaibo Qu, Lei Tang

“…To address the issues of high energy costs and inadequate system response speed in complex electricity markets, we propose an electricity price optimization model. This model combines an improved Particle Swarm Optimization algorithm, Quantum-behaved Particle Swarm Optimization, and the Shuffle Frog Leaping Algorithm. …”
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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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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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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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