Low-carbon optimization planning method for integrated energy system based on DG uncertainty affine model by JIANG Tao, XU Cong, JIA Shaohui, WANG Shen, ZHANG Yajian

“…Then, based on the differential evolution-particle swarm optimization algorithm, the established low-carbon planning model of the integrated energy system was solved to avoid the algorithm from falling into local optimality during the optimization process. …”
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Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm by Gaoyang Liang, Mingqiang Xing, Jianqiang Zhao

“…The results indicate that all three driving forces significantly enhance the overall level of urban-rural integration, with the most substantial improvements observed in economic and social integration. …”
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Dynamic reconfiguration of the distribution systems with Load Duration Curve (LDC) model for reducing the losses and improving the voltage profile by Sana Sadeghi, Alireza Jahangiri, Ahmad Ghaderi Shamim

“…Simulations were conducted on the well-established IEEE 33-bus test system, employing MATLAB software in conjunction with a genetic algorithm to minimize losses and optimize voltage profiles. …”
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A novel swarm intelligence-based approach for solving optimal power flow problems in modern power systems by Haewon Byeon, Wajdi Alghamdi, Munni Evin, M. Sucharitha, D. David Neels Ponkumar, A. Prakash, J. Sunil

“…In order to solve the optimum power flow difficulties related to the C-UPFC, this research suggested an Improved Pelican optimization algorithm (IPOA). Install the superior flexible AC transmission system (FACTS) in accordance with the transmission line (TL) in a series configuration to provide independent voltage control that combines power flow regulation. …”
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OPTIMIZATION OF FUZZY INVENTORY MANAGEMENT IN INDUSTRIAL PROCESSES USING DEEP LEARNING ALGORITHMS: A HYBRID APPROACH FOR ENHANCING DEMAND FORECASTING AND SUPPLY CHAIN EFFICIENCY by K. Kalaiarasi*, S. Swathi

“…A mathematical model and algorithmic implementation demonstrate the approach’s effectiveness and a numerical example highlights improvements in inventory control, including reduced holding costs. …”
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Integrating GIS, 3D-Isovist, and an NSGA-II multi-objective optimization algorithm for automation of design process in urban parks and public open spaces by Karim Zandniapour, Akram Soroush, Ehsan Khezerlu Agdam, Haniyeh Sanaieian

“…The results showed that the NSGA-II was able to solve the complex design problem with 185 trees and 66 observers. The algorithm produced a Pareto-frontier consisting of four optimal solutions that, compared to the existing state of the park, showed more than 18% and 12 % improvement according to Tree View and Building View, respectively. …”
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Internet of things driven object detection framework for consumer product monitoring using deep transfer learning and hippopotamus optimization by Amnah Alshahrani, Mukhtar Ghaleb, Hany Mahgoub, Achraf Ben Miled, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Hasan Beyari, Sultan Alanazi

“…Additionally, the hippopotamus optimization algorithm (HOA)-based hyperparameter selection model is implemented to improve the classification result of the CAE technique. …”
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A Feasibility Study of a Virtual Power Line Device to Improve Hosting Capacity in Renewable Energy Sources by Seong-Eun Rho, Sung-Moon Choi, Joong-Seon Lee, Hyun-Sang You, Seung-Ho Lee, Dae-Seok Rho

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Efficient Technique for Joint Parameter Estimation of Mixed Far Field Targets and Near Field Jammers in Phased Array Radar by Fawad Zaman, Sadiq Akbar, Zohaib Akhtar, Gridsada Phanomchoeng

“…A novel approach based on the Gradient Based Optimizer (GBO) algorithm and Marine Predators Algorithm (MPA) is proposed to estimate jointly the unknown parameters related to the far field targets and near field jammers. …”
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Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users by Christopher Meaney, Xuesong Wang, Jun Guan, Therese A. Stukel

“…Hyper-parameter tuning using any HPO algorithm/sampler improved model discrimination (AUC=0.84), resulted in models with near perfect calibration, and consistently identified features predictive of high-need high-cost health care users. …”
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Local corner smoothing based on deep learning for CNC machine tools by Bai Jiang, Rong Sun, Ze-long Li, Liang Xu, Huang Liao, Xiao-yan Teng, Bing Li

“…Considering the influence of population size and computational resources on intelligent optimization algorithms, a deep learning algorithm (the Double-ResNet Local Smoothing (DRLS) algorithm) is proposed to further improve optimization efficiency. …”
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Multi-Stage and Multi-Objective Optimization of Solar Air-Source Heat Pump Systems for High-Rise Residential Buildings in Hot-Summer and Cold-Winter Regions by Zhen Wang, Jiaxuan Wang, Chenxi Lv

“…Next, the GenOpt program and the Hooke–Jeeves algorithm are used to perform the first stage of optimization with the lowest annual cost value as the objective function. …”
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Double-Layer Optimization Mechanism for Multi-Area OPF Considering Valve-Point Loading Effect by Jizhong Zhu, Cong Zeng, Yun Liu, Xuancong Xu

“…In terms of the multi-area optimal power flow (OPF) problem, the optimized objectives are always a fuel cost function expressed by a second-order polynomial. …”
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SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study by Abrar Yaqoob, Navneet Kumar Verma, Mushtaq Ahmad Mir, Ghanshyam G. Tejani, Nashwa Hassan Babiker Eisa, Hind Mamoun Hussien Osman, Mohd Asif Shah

“…Abstract In this study, we propose a novel approach for breast cancer classification that integrates the Seagull Optimization Algorithm (SGA) for feature selection with the Random Forest (RF) classifier for effective data classification. …”
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Facilitating Circular Transition in the Construction Industry: Optimizing a Prefabricated Construction Site Layout Using a Novel BIM-Integrated SLP-GA Model by Lin Wang, Qi Wang, Shuxiu Dong, Yue Cao, Liang Wang

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Optimal Configuration Method for Electric-thermo-hydrogen System Considering Safety Risks by Chouwei NI, Yang CHEN, Xuesong ZHANG, Da LIN, Kaijian DU, Jian CHEN

“…Furthermore, the safety risk coefficient is used to convert the safety risk of the hydrogen storage tank into the objective function. The optimal configuration model of the ETHS is then established with the system investment cost, operation cost, and safety risk as optimization objectives, and the tabu chaotic quantum particle swarm optimization (TCQPSO) algorithm is employed to solve the model. …”
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An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang, Junjie Lei

“…Next, the collected received signal strength indication (RSSI) data are processed using Kalman filtering and Min-Max normalization, suppressing signal fluctuations and accelerating the gradient descent convergence of the distance measurement model. Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. …”
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Towards Automated Cadastral Map Improvement: A Clustering Approach for Error Pattern Recognition by Konstantinos Vantas, Vasiliki Mirkopoulou

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Identifying, Evaluating and Ranking Effective Factors in Improving the Quality of War Tourism in Iran (Rahyan Noor Travels) by Mohammad Ghasemi, Mohammad Mehdi Mohtadi

“…Due to the uncertainty in determining the importance of the factors based on every criterion, ranking is based on the Fuzzy TOPSIS algorithm. Findings: According to the results, optimizing camp time has been selected as the first and most crucial factor, with a relative proximity index of 0.53467. …”
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Robust Optimization of Active Distribution Networks Considering Source-Side Uncertainty and Load-Side Demand Response by Renbo Wu, Shuqin Liu

“…The simulation results based on the improved IEEE33 bus system show that the proposed method reduces the operation cost by 5.7% compared with the traditional robust optimization, and the cut-load capacity is significantly reduced at a confidence level of 0.95. …”
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