Artificial Neural Network - Multi-Objective Genetic Algorithm based optimization for the enhanced pigment accumulation in Synechocystis sp. PCC 6803 by Namrata Bhagat, Guddu Kumar Gupta, Amritpreet Kaur Minhas, Deepak Chhabra, Pratyoosh Shukla

“…Furthermore, these machine learning tools can be used as a model to improve and optimize the yields for other metabolites production. …”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…The proposed GAT model outperformed the state-of-the-art MPGCN and DNN models, achieving improvement of 86.33% and 62.71%, respectively, under 60% DG penetration condition. …”
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Performance assessment of basalt fibre concrete under freeze-thaw cycles using hybrid long short-term memory models by Qingguo Yang, Honghu Wang, Qigui Yi, Liuyuan Zeng, Rui Xiang, Longfei Guan, Jiawei Cheng, Keling Chen, Yunhao Li

“…The results demonstrate that swarm intelligence optimization algorithms (SIOA) significantly enhance the prediction accuracy and stability of the LSTM model. …”
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Inversion of permeability coefficient based on adaptive differential hybrid butterfly particle algorithm by Zhao YANG, Donglin DONG, Yuqi CHEN, Rong WANG

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Optimum design of double tuned mass dampers using multiple metaheuristic multi-objective optimization algorithms under seismic excitation by Fateme Zamani, Sayyed Hadi Alavi, Mohammadreza Mashayekhi, Ehsan Noroozinejad Farsangi, Ataallah Sadeghi-Movahhed, Ali Majdi

“…The tuning process is carried out using a combination of Pareto front derived from seven multi-objective metaheuristic optimization algorithms with two objectives. The proposed methodology is applied to a 10-floor case study, using ground acceleration time histories to evaluate its seismic performance. …”
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Study on Energy-saving Control of Large Central Air-conditioning System Based on BAS-PSO by Chen Yang, Yao Ye

“…The experimental test results show that the optimization algorithm can achieve a 14.6% energy saving rate, saving 153.15 kW of energy, which proves that the optimal control model and optimization algorithm have reliable application prospects.…”
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Optimizing CNC turning of AISI D3 tool steel using Al₂O₃/graphene nanofluid and machine learning algorithms by Leta Daba Gemechu, Dame Alemayehu Efa, Robsan Abebe

“…The Response Surface Methodology (RSM), Back Propagation (BP) neural networks, and Genetic Algorithms (GA) will be utilized to model and predict optimal turning parameters to enhance surface quality and manage tool tip temperature. …”
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Optimal sleep time controller based on traffic prediction and residual energy in duty-cycled wireless sensor networks by Haibo Luo, Minghua He, Zhiqiang Ruan, Xiaxia Zeng

“…In duty-cycled wireless sensor networks, energy efficiency and packet latency are two most important metrics in the design of medium access control and routing algorithms. …”
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Encoding local label correlations in multi-instance multi-label learning with an improved multi-objective particle swarm optimization by Xiang Bao, Fei Han, Qinghua Ling

“…In this paper, a MIML algorithm encoded with local label correlations with an improved Multi-Objective Particle Swarm Optimization (MIML-MOPSO-LLC) is proposed to address the above problems. …”
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Identification of maize kernel varieties based on interpretable ensemble algorithms by Chunguang Bi, Chunguang Bi, Xinhua Bi, Jinjing Liu, Hao Xie, Shuo Zhang, He Chen, Mohan Wang, Lei Shi, Lei Shi, Shaozhong Song

“…IntroductionMaize kernel variety identification is crucial for reducing storage losses and ensuring food security. Traditional single models show limitations in processing large-scale multimodal data.MethodsThis study constructed an interpretable ensemble learning model for maize seed variety identification through improved differential evolutionary algorithm and multimodal data fusion. …”
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Classification algorithm for imbalance data of ECG based on PSOFS and TSK fuzzy system by Xinhui LI, Qing SHEN, Xiongtao ZHANG

“…A new classification model of electrocardiogram (ECG) signal based on particle swarm optimization feature selection (PSOFS) and TSK (Takagi-Sugeno-Kang) fuzzy system was proposed, i.e., parallel ensemble fuzzy neural network based on PSOFS and TSK (PE-PT-FN), which was used for ECG prediction.Each class sample in the training set was randomly sampled, and the samples obtained by randomly sampled were added.Then, the feature selection method PSOFS was carried out independently and parallelly.In PSOFS, particles that were random initial positions represent different feature subsets and converge to the optimal positions after many iterations.Each subset had a corresponding feature subset.Several groups of TSK fuzzy neural network (TSK-FNN) were trained by each feature subset in parallel.Medical researchers could effectively find the correlation between ECG signal data and different types of disease through the interpretability of the fuzzy system and the feature subsets by the PSOFS algorithm.Experiments prove that PE-PT-FN greatly improves the macro-R to 92.35% while retaining interpretability.…”
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Optimizing Vehicle Routing for Perishable Products with Time Window Constraints: by Rifqi Fauzi, Adi Priansyah, Paskalis Krisna Puspadewa, Syifa Maulvi Zainun Awal, Huu Tho Nguyen, Achmad Pratama Rifai

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Design of optimized single-switch capacitor cell balancing for EV battery management by Anjan N. Padmasali, Savitha G. Kini, Arun P. Parameswaran

“…However, there are possible modifications to them that may lead to algorithms with improved results. Two algorithms are explored for a four-series connected Li-ion cell battery system. …”
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Analysis of Unmanned Surface Vehicles Heading KF-Based PI-(1+PI) Controller Using Improved Spider Wasp Optimizer by Xiaoyu Li, Xiangye Zeng, Jingyi Wang, Qi Li, Baoshuo Fan, Qi Zeng

“…A transfer function model of the USV heading system is established using voyage data, with ISWO optimizing its parameters, achieving a 5.67% reduction in mean squared error (MSE) compared to the original Spider Wasp Optimizer and outperforming classical algorithms like Arithmetic Optimization Algorithm (AOA), Crayfish Optimization Algorithm (COA), and Marine Predators Algorithm (MPA). …”
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Improved double DQN with deep reinforcement learning for UAV indoor autonomous obstacle avoidance by Ruiqi Yu, Qingdang Li, Jiewei Ji, Tingting Wu, Jian Mao, Shun Liu, Zhen Sun

“…The algorithm enhances the perception and learning capabilities by optimizing the network model and employs a dynamic exploration strategy that encourages exploration in the early stage and reduces it later to accelerate convergence and improve efficiency. …”
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Integrating Large Language Models and Optimization in Semi- Structured Decision Making: Methodology and a Case Study by Gianpaolo Ghiani, Gianluca Solazzo, Gianluca Elia

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Design of a liquid cooled battery thermal management system using neural networks, cheetah optimizer and salp swarm algorithm by Anjan Kumar, Laith Hussein Jasim, Padmanabha Vijaya, Dipak Patel, J. Gowrishankar, R. Sivaranjani, Ankur Srivastava, Mayank Kundlas, Sarbeswara Hota, Banafshe Hamidi

“…In the first phase, predictive modeling was performed using multilayer perceptron neural networks (MLPNN) optimized by three metaheuristic algorithms: cheetah optimizer (CO), grey wolf optimizer (GWO), and marine predators algorithm (MPA). …”
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Research on the Trusted Traceability Model of Taishan Tea Products Based on Blockchain by Kangchen Liu, Pingzeng Liu, Shuaishuai Gao

“…The optimized SM2 encryption algorithm is introduced, and the execution efficiency of the encryption algorithm is improved by the concurrent processing framework, which guarantees the security and transmission speed of the data. …”
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Advancement of electric vehicle technologies, classification of charging methodologies, and optimization strategies for sustainable development - A comprehensive review by Vikram Goud Madaram, Pabitra Kumar Biswas, Chiranjit Sain, Sudhakar Babu Thanikanti, Praveen Kumar Balachandran

“…The review evaluates algorithms and mathematical models that maximize efficiency, reduce costs, and improve charging resource accessibility. …”
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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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