Joint energy efficiency and spectral efficiency optimization algorithm for UDN under the restriction of interference threshold and backhaul capacity by Xuanli WU, Xu CHEN

“…Aiming at the scenarios which consider the constraint of backhaul capacity restriction and interference threshold in ultra-dense networks (UDN),an integer linear programming (ILP) and Lagrangian dual decomposition (LDD) based joint optimization algorithm of energy efficiency and spectrum efficiency was proposed.In the proposed algorithms,the user association problem with the constraint of limited backhaul capacity was modelled as an ILP problem and then finished the connection between the user and the base station of microcell by solving this problem with dynamic programming method.Therefor,Lagrangian dual decomposition (LDD) was applied in an iteration algorithm for spectrum resource allocation and power allocation.The simulation results show that compared with traditional schemes,the proposed algorithm can significantly improve the energy efficiency and spectrum efficiency of system and use the microcell’s load capacity more efficiently.…”
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Electrical Equivalent Circuit Parameter Estimation of Commercial Induction Machines Using an Enhanced Grey Wolf Optimization Algorithm by Premkumar Manoharan, Sowmya Ravichandran, Jagarapu S. V. Siva Kumar, Mustafa Abdullah, Tan Ching Sin, Tengku Juhana Tengku Hashim

“…Extensive simulation validation was conducted across various induction motor models, including eight commercial motors, and demonstrated that AWGWO consistently outperforms state-of-the-art algorithms in terms of convergence speed, solution accuracy, and robustness in multimodal optimization landscapes. …”
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Optimized control of parallel heat pump units based on the satin bower bird algorithm in a distributed architecture by Sijia Zhang, Jiangtao Xi, Anjun Zhao, Jun Liu, Yuping Zhang

“…The Distributed Satin Bowerbird Optimization (D-SBO) algorithm is proposed to address the load optimization distribution problem in parallel heat pump units within MDBHE. …”
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Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe, Reena Jangid

“…PLO undergoes performance testing against nine established optimization techniques including GSA, DE, PSO, MFO, ACOR, MVO, WOA, SCA, and JAYA through six PEMFC models which include BCS 500 W, Nedstack 600 W PS6, SR-12 W, Horizon H-12, Ballard Mark V, and STD 250 W Stack. …”
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Geological disaster risk assessment based on remote sensing, GIS, and a multi-strategy improved GWO-optimized Elman neural network by Kuayue Chen, Fuhong Bai, Ting Wang, Yingmei Su, Baoyun Wang

“…To improve the accuracy and intelligence of geological disaster risk assessment, this study proposes a novel method based on a Multi-strategy Improved Grey Wolf Optimization algorithm combined with the Elman Neural Network (MIGWO-Elman). …”
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Mathematical model of on-demand route formation for public transport based on individual passenger requests in low-density population area by Svetlana S. Titova, Andrey V. Ostroukh

“…Various route optimization algorithms were investigated, and the most suitable method was selected for solving the stated problem. …”
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Improved faster R-CNN for steel surface defect detection in industrial quality control by Yuefeng Leng, Jiazhi Liu

“…Evaluated on the NEU-DET dataset, the optimized model achieves a mean average precision (mAP) of 80.2%-yielding a 12.6% improvement over the baseline-while increasing detection speed by 40.9%. …”
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Diagnosing schizophrenia with routine blood tests: a comparative analysis of machine learning algorithms by Yavuz Selim Ogur, Ayse Erdogan Kaya, Nur Banu Ogur, Beyza Erdogan Akturk

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Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly Constraints by Tingting Qu

“…For this model, an improved greedy algorithm was combined to solve it, and particle swarm optimization algorithm was introduced to enhance the local and global search capabilities of the distributed scheduling system, effectively addressing the computational complexity in large-scale production environments. …”
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Hybrid Paddy disease classification using optimized statistical feature based transformation technique with explainable AI by M Amudha, Brindha K

“…To enhance predictive performance by transforming features, an improved Owl Search Optimization (IOSO) algorithm is used. …”
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Study of Fair Strategy for Merchant Self-Operated Takeaway Delivery Based on Delivery Plan Optimization by Jing Chen, Chengbo Guo, Jiahua Kou, Jiali Du, Shufa Sun, Yanling Guo

“…This study presents a mathematical model for merchant-operated takeaway delivery, using an improved ant colony algorithm integrated with K-means to cluster customer locations and determine optimal routes. …”
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Classification of Tropical Cyclone Tracks in the Northwest Pacific Based on the SD-K-Means Model by Nan Xu, Baisong Yang, Jia Ren

“…This study proposes an improved SD-K-Means clustering algorithm for classifying TC tracks. …”
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Low Carbon Economic Dispatch of Power System Based on Multi-Region Distributed Multi-Gradient Whale Optimization Algorithm by Linfei Yin, Yongzi Ye, Xiaoping Xiong, Jiajia Chai, Hanzhong Cui, Haoyuan Li

“…This study establishes a multi-region distributed optimization model and combines the multi-region distributed optimization model with a multi-gradient optimization algorithm to propose a multi-region distributed multi-gradient whale optimization algorithm (MRDMGWOA). …”
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Optimizing Multi-Echelon Delivery Routes for Perishable Goods with Time Constraints by Manqiong Sun, Yang Xu, Feng Xiao, Hao Ji, Bing Su, Fei Bu

“…The results demonstrate that the initial solutions obtained through the k-medoids clustering algorithm based on spatio-temporal distance improved the overall cost optimization by 1.85% and 4.74% compared to the other two algorithms. …”
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A new CNN deep learning model for computer-intelligent color matching by He Zhibin, Tan Yanmei, Li Sa

“…Besides, based on the optimized algorithm, an intelligent color-matching model was constructed. …”
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Optimization design on process parameters of copper wire bonding for power modules by HU Biao, CHENG Lanxian, LI Zhenling, DAI Xiaoping

“…In order to improve the copper wire bonding performance of the power modules, an optimization design scheme of process parameters for copper wire bonding was proposed by using the six-factor five-level orthogonal test method, and combining the back propagation (BP) neural network and genetic algorithm (GA). …”
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Structure Design and Optimization of Self-locking Under-actuated Gripper by Shuting He, Yi Shen, Xianling Dai, Beibei Qiu, Xianfeng Pan, Mingxin Yuan

“…A structural parameter optimization model is established according to the balance of the clamping force of each gripper knuckle， and a genetic algorithm is introduced to realize the parameter optimization. …”
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Parameter Adaptive Manta Ray Foraging Optimization for Global Continuous Optimization Problems and Parameter Estimation of Solar Photovoltaic Models by Zhentao Tang, Kaiyu Wang, Yongxuan Yao, Mingxin Zhu, Lan Zhuang, Huiqin Chen, Jing Li, Li Yan, Shangce Gao

“…Furthermore, to enhance population diversity and avoid premature convergence, a randomly selected individual from the top $$ G $$ G high-quality solutions replaces the current best individual in the somersault foraging behavior. Based on these improvements, a parameter adaptive manta ray foraging optimization (PAMRFO) algorithm is developed. …”
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Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…Moreover, This study develops the proposed EffiXNet, a more refined version of EfficientNet augmented with self-attention mechanisms, dynamic convolutions, improved normalization methods, and Sparrow Search Optimization Algorithm for hyperparameter optimization. …”
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Wakeup strategy based on multi-objective optimization for fixed relay nodes by Xue-bin MA, Ai-li LI, Xiao-juan ZHANG

“…In order to deal with the “tidal effect” when people move in the city and solve the problem of high energy consumption of fixed relay nodes in opportunistic networks,a wakeup strategy of multi-objective optimization was proposed,which made use of the message forward ability and energy consumption of fixed relay nodes.This strategy used energy efficiency as the indicator to make the nodes awake,and deployed a network revenue-energy consumption model to resolve the contradiction between energy consumption and message forward ability.As the selection problem of awake relay nodes was a NP-hard problem,genetic algorithm was used to select proper fixed relay nodes to keep awake.In this process,selection operator was improved to make the algorithm converge to solution space quickly.Experiments show that the proposed wakeup strategy can guarantee the successful rate of message transmission and improve the average message forwarding capabilities of fixed relay nodes by consuming a unit energy.…”
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