Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization by Yuzhi YAN, Youming LI, Guili ZHOU, Yaohui WU

“…Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.…”
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Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization by Yuzhi YAN, Youming LI, Guili ZHOU, Yaohui WU

“…Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.…”
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Optimization of Combat Resource Allocation Based on Restricted Tournament Selection Social Genetic Algorithm by Shandong Yuan, Yun Ren, Han Zhou, Yongjing Cheng, Kai Yan

“…In addition, we innovatively incorporate the concept of ‘group effect’ from sociology, adding a socialization operator to the algorithm to accelerate convergence and improve the quality of optimal solutions. …”
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A Bi-Objective Optimal Scheduling Method for the Charging and Discharging of EVs Considering the Uncertainty of Wind and Photovoltaic Output in the Context of Time-of-Use Electrici... by Xinfu Pang, Wen Jia, Haibo Li, Qingzhong Gao, Wei Liu

“…Finally, the model was solved using an improved multi-objective barebones particle swarm optimization algorithm. …”
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Fleet management algorithm for enhancing environmental friendliness of maritime delivery by Андрій Романов

“…The study proposes an improved algorithm for constructing maritime cargo delivery routes using a genetic algorithm with a speed optimization step. …”
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Research on the optimization of optimal blasting parameters and fragmentation control based on coal seam geological conditions by Zhouquan Liao, Xiaohua Ding, Mingzhi Liang, Jiangfeng Li, Zhongao Yang, Xin Liu, Bin Li, Yan Zhang

“…Abstract Open-pit coal mining often employs loosening blasting, with perforation blasting accounting for a significant portion of the coal seam mining costs. For coal of the same quality, the price of lump coal is much higher than that of crushed coal. …”
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Trajectory Similarity Algorithm Based on DTW and Trajectory Point Compression by GAO Wei, QIAN Chengyang, ZHANG Qi, XIE Hongquan

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Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model by Bo Zhou, Erchao Li, Wenjing Liang

“…Finally, a combination algorithm of improved robust optimization over time (ROOT) and CPLEX is proposed to solve the established game model. …”
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Load optimization of cogeneration units based on intuitive multi-objective fish swarm algorithm by Xueqiang Shen, Jiaxin Wang

“…A cogeneration unit model incorporating operational characteristics and historical data demonstrates the method’s efficacy: multi-objective balance is maintained across iterations, achieving a 1.41% thermoelectric load increase and 1.54% optimal coal consumption reduction. The algorithm reduces heat/electricity losses and operational costs under diverse conditions while enhancing load utilization rates. …”
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Optimization Design Method of Pipe-Insulating Joints Based on Surrogate Model and Genetic Algorithm by Chen Guo, Zheng Yang, Jianbo Dong, Yanchao Yue, Linjun Tian, Ping Ma

“…This improves the computational efficiency of the optimization algorithm by establishing a surrogate model, which can be used to optimize the dimensions of insulation joints.…”
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A novel solid waste instance creation for an optimized capacitated vehicle routing model using discrete smell agent optimization algorithm by Ahmed T. Salawudeen, Olusesi A. Meadows, Basira Yahaya, Muhammed B. Mu'azu

“…The developed model was optimized using a new discrete smell agent optimization (SAO) algorithm and compared to firefly algorithm (FA) and particle swarm optimization (PSO). …”
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Post-Anesthesia Care Unit (PACU) readiness predictions using machine learning: a comparative study of algorithms by Shahnam Sedigh Maroufi, Maryam Soleimani Movahed, Azar Ejmalian, Maryam Sarkhosh, Ali Behmanesh

“…Abstract Introduction Accurate and timely discharge from the Post-Anesthesia Care Unit (PACU) is essential to prevent postoperative complications and optimize hospital resource utilization. …”
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A quasi-opposition learning and chaos local search based on walrus optimization for global optimization problems by Yier Li, Lei Li, Zhengpu Lian, Kang Zhou, Yuchen Dai

“…The study aims to prevent premature convergence to local optima and enhance the diversity of the population by integrating the quasi-oppositional-based learning mechanism into the original Walrus Optimization (WO) algorithm, thereby improving the global search capability and expanding the search range. …”
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Ultra Short-Term Charging Load Forecasting Based on Improved Data Decomposition and Hybrid Neural Network by Shaoyang Yin, Zhaohui Chen, Wanyuan Liu, Zhiwen Su

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Dynamic Optimization of Xylitol Production Using Legendre-Based Control Parameterization by Eugenia Gutiérrez, Marianela Noriega, Cecilia Fernández, Nadia Pantano, Leandro Rodriguez, Gustavo Scaglia

“…This dimensionality reduction improves the robustness of the optimization by decreasing the likelihood of convergence to local optima while also reducing the computational cost and enhancing feasibility for implementation. …”
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Exponential Improvements in the Simulation of Lattice Gauge Theories Using Near-Optimal Techniques by Mason L. Rhodes, Michael Kreshchuk, Shivesh Pathak

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Optimizing energy cost in the residential sector through home energy management systems in a smart grid environment by Nabeeha Qayyum, Umar Jamil, Anzar Mahmood

“…The results show that GA achieved a 48% cost reduction compared to PSO, with significant peak load reduction and improved energy optimization when integrated with PV systems. …”
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An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem by Jianxia Zhang, Jianxin Zhang, Feng Zhang, Minglu Chi, Linbin Wan

“…In addition, two different kinds of practical examples were also adopted for algorithm evaluation. From the simulation results, it can be seen clearly that the costs of electric-power generation gained were the lowest compared with the results of particle swarm optimization algorithm, improved chaos particle swarm optimization algorithm, and symbiotic organisms search algorithm, well demonstrating the effectiveness of the improved symbiosis particle swarm optimization algorithm in solving the economic load dispatch problem.…”
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Low-carbon economic dispatching of integrated energy system based on improved white shark algorithm by LI Haobo, CUI Shuangxi, FAN Weijie

“…The white shark algorithm is improved by integrating directed differential mutation and other strategies to solve the low-carbon economic scheduling model of the integrated energy system, and the optimal scheduling scheme of each time period is obtained by combining the advantages and disadvantages of the solution distance method. …”
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Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest by X Peng, C Chen, L Yu, X Kong, B Sun

“…A baseline Random Forest (RF) model achieved 94.01% diagnostic accuracy for broiler diseases. To optimize performance, we developed RF_WOA_DBO-an integrated algorithm combining RF with enhanced Whale Optimization Algorithm (WOA) for global feature selection and modified Dung Beetle Optimizer (DBO) for local parameter tuning. …”
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