A quasi oppositional forensic based investigation algorithm for optimizing distributed generation placement and sizing in power distribution systems by Binaya Kumar Malika, Vivekananda Pattanaik, Subhasis Panda, Binod Kumar Sahu, Pravat Kumar Rout, Mohit Bajaj, Vojtech Blazek, Lukas Prokop, Stanislav Misak

“…This manuscript addresses these issues by proposing a novel quasi-oppositional forensic-based investigation (QOFBI) algorithm, an evolutionary meta-optimization technique designed to optimize the location and sizing of DGs under various operating conditions, while adhering to system constraints. …”
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Rotation Correction Algorithm Based on Polar Harmonic Fourier Moments and Optimization of Color Image Security Quantization Watermarking Scheme by Yuli Yang, Meiru Jiang, Xiufang Feng, Chenchen Lu, Yongle Chen, Shuang Zhou, Hao Zhang

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Comprehensive optimization of active and reactive power scheduling in smart microgrids by accounting for line transmission losses using genetic algorithm by F.Z. Zahraoui, H.E. Chakir, M. Et-taoussi, H Ouadi

“…The grid-connected SMG consists of photovoltaic (PV) cells, BSS, and residential loads. A Genetic Algorithm (GA)-based method is proposed to optimize power management in three scenarios: (i) active power only (AOM), (ii) active and reactive power without line losses (ARM), and (iii) active and reactive power considering line losses (ARLM). …”
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Multi-Degree Reduction of Said–Ball Curves and Engineering Design Using Multi-Strategy Enhanced Coati Optimization Algorithm by Feng Zou, Xia Wang, Weilin Zhang, Qingshui Shi, Huogen Yang

“…To enhance performance further, we propose a multi-strategy enhanced coati optimization algorithm (MSECOA). This algorithm utilizes a good point set combined with opposition-based learning to refine the initial population distribution, employs a fitness–distance equilibrium approach alongside a dynamic spiral search strategy to harmonize global exploration with local exploitation, and integrates an adaptive differential evolution mechanism to boost convergence rates and robustness. …”
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Optimizing a Hybrid Controller for Automotive Active Suspension System by Using Genetic Algorithms With Two High Level Parameters by Vu Van Tan, Do Trong Tu, Nguyen Van Vinh, Pham Tat Thang, Andras Mihaly, Peter Gaspar

“…Specifically, the ride comfort has improved from 60% to 80%, while the road holding has improved from 10% to 15%. …”
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Dual-layer scheduling coordination algorithm for power supply guarantee using multi-objective optimization in spot market environment by Xuanyuan Wang, Xu Gao, Zhen Ji, Wei Sun, Bo Yan, Bohao Sun

“…The experimental results show that, compared to the benchmark strategy, the proposed algorithm achieves a cost savings of 8.33% while ensuring a reliable power supply. …”
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Optimization of Francis turbine runner based on analytic hierarchy process – entropy weight method and multi-objective Lichtenberg algorithm by Xiaobo Zheng, Wei Wang, Yaping Zhao, Hao Liang, Pengcheng Guo, Zhihua Li

“…To address these issues, this study develops a multi-condition, multi-objective optimization platform for a Francis turbine runner based on the Analytic Hierarchy Process-Entropy Weight (AHP) method and the Multi-Objective Lichtenberg Algorithm (MOLA). …”
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Estimating Daily Reference Crop Evapotranspiration in Northeast China Using Optimized Empirical Models Based on Heuristic Intelligence Algorithms by Zongyang Li, Zhengxin Zhao, Liwen Xing, Lu Zhao, Ningbo Cui, Huanjie Cai

“…By using the least square method (LSM) and three population heuristic intelligent algorithms—a genetic algorithm (GA), a particle swarm optimization algorithm (PSO), and a differential evolution algorithm (DE)—the parameters of eleven kinds of models were optimized, respectively, and the ETo estimation model suitable for northeast China was selected. …”
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The quick crisscross sine cosine algorithm for optimal FACTS placement in uncertain wind integrated scenario based power systems by Sunilkumar P. Agrawal, Pradeep Jangir, Laith Abualigah, Sundaram B. Pandya, Anil Parmar, Absalom E. Ezugwu, Arpita, Aseel Smerat

“…The Quick Crisscross Sine Cosine Algorithm (QCSCA) was developed to address the challenges of solving the Optimal Power Flow (OPF) problem in power systems that integrate renewable energy sources and Flexible AC Transmission Systems (FACTS) devices. …”
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Hyperparameter Optimization for Problem-Based Custom CNN Architectures Using a Smart Grid Search Method by H. Aktas

“…The proposed method was also compared with Bayesian optimization using a similar search space. While Bayesian optimization achieved the same highest test accuracy (99.22%), it produced a model that was 3.7 times larger. …”
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Enhanced energy-efficient cluster-based routing with spotted hyena optimization in heterogeneous WSNs by Ved Prakash, Suman Pandey, Biswa Mohan Sahoo

“…The proposed SHO-CH method seeks to improve energy efficiency and prolong the lifespan of the network by optimizing the development of clusters and routing. …”
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Solving the Economic Load Dispatch Problem by Attaining and Refining Knowledge-Based Optimization by Pravesh Kumar, Musrrat Ali

“…The Static Economic Load Dispatch (SELD) problem is a paramount optimization challenge in power engineering that seeks to optimize the allocation of power between generating units to meet imposed constraints while minimizing energy requirements. …”
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Multi-objective optimization and parameter sensitivity study on microreactor nuclear power systems by Ersheng You, Yiyi Li, Jianjun Xu, Dianchuan Xing, Haochun Zhang

“…The PSO algorithm code was used to calculate and compare the benchmark case of MRNPS, and the optimized Pareto optimal solution set was obtained. …”
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Hybrid Path Planning Method for USV Based on Improved A-Star and DWA by Yan Liu, Zeqiang Sun, Junhe Wan, Hui Li, Delong Yang, Yanping Li, Wei Fu, Zhen Yu, Jichang Sun

“…An advanced Bézier curve smoothing method is also proposed, which adaptively selects control points to improve path smoothness and driving stability. By incorporating these improvements, the enhanced A-Star algorithm is combined with DWA to facilitate dynamic obstacle avoidance while generating global paths. …”
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Adaptive Sharding for UAV Networks: A Deep Reinforcement Learning Approach to Blockchain Optimization by Kaiyin Lu, Xinguang Zhang, Tianbo Zhai, Mengjie Zhou

“…Our research extends beyond improving data transmission rates to encompass an enhanced Asynchronous Advantage Actor–Critic algorithm, tailored to address long-term optimization objectives in aerial networks. …”
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A new smart charging electric vehicle and optimal DG placement in active distribution networks with optimal operation of batteries by Bilal Naji Alhasnawi, Marek Zanker, Vladimír Bureš

“…Thirdly, this paper proposes an optimization technique based on the Mountain Gazelle Optimizer (MGO), Improved Beluga Whale Optimization (IBWO), and Arithmetic Optimization Algorithm (AOA) for determining the optimal DGs in radial distribution systems. …”
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Indirect tuning of a complementary orientation filter using velocity data and a genetic algorithm by Dariusz Maton, John T. Economou, David Galvão Wall, Irfan Khan, Robert Cooper, David Ward, Simon Trythall

“…In this paper, the accuracy of inertial sensor orientation relative to the level frame is improved through optimal tuning of a complementary filter by a genetic algorithm. …”
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Enhanced COVID-19 Optimization Algorithm for Solving Multi-Objective Optimal Power Flow Problems with Uncertain Renewable Energy Sources: A Case Study of the Iraqi High-Voltage Gri... by Basim ALBaaj, Orhan Kaplan

“…This paper introduces an enhanced version, the enhanced COVID-19 optimization algorithm (ENHCOVIDOA), designed to improve the performance of the original method. …”
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Improved RRT-Based Obstacle-Avoidance Path Planning for Dual-Arm Robots in Complex Environments by Jing Wang, Genliang Xiong, Bowen Dang, Jianli Chen, Jixian Zhang, Hui Xie

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The algorithm and implementation of an extension to LLVM for solving the blocking between instruction sink and division-modulo combine by YungYu Zhuang, Ting-Wei Lin, Yin-Jung Huang

“…The results demonstrate that our approach effectively addresses the blocking problem without conflicting with other optimization algorithms, solely impacting problematic instructions while leaving normal ones unaffected.…”
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