Reducing hydrogen consumption in hybrid electric vehicles using aquila optimization algorithm by A.M. Nassef, H.E. Ghadbane, E.T. Sayed, H. Rezk

“…The aquila optimization algorithm is one of the most recent and efficient algorithms. …”
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Spike-RISC: Algorithm/ISA Co-Optimization for Efficient SNNs on RISC-V by Ipek Akdeniz, Sandy A. Wasif, Paul R. Genssler, Hussam Amrouch

“…This paper proposes Spike-RISC, a holistic algorithm/instruction set architecture (ISA) co-optimization for efficient SNN inference. …”
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Innovative Hybrid Algorithm for Solving Vehicle Routing Problem with Time Window by A.M. Rahimi, B. Yadegari, M. Aboutalebi Esfahani

“…The proposed algorithm is suitable for transportation and logistics systems with limited customers and leads to cost reduction, improved delivery times, and increased service quality.…”
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Dynamic optimization of solar DG and shunt capacitor placement to mitigate the impact of EV charging stations on power distribution network by T. Yuvaraj, M. Thirumalai, T.D. Suresh, Sudhakar Babu Thanikanti, Mohammad Khishe

“…Simulation results confirm the superior performance of QRSMA in improving voltage profiles, reducing power losses, and achieving better computational efficiency compared to conventional optimization algorithms. …”
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GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation by Eman Mahmoud, Salem Alkhalaf, Tomonobu Senjyu, Masahiro Furukakoi, Ashraf Hemeida, Ghada Abozaid

“…However, multilevel thresholding, a widely used segmentation technique, suffers from high computational complexity due to the exhaustive search for optimal thresholds. This paper addresses this challenge by proposing a hybrid Genetic Algorithm-Archimedes Optimization Algorithm (GAAOA), further enhanced with a Lévy flight function (GAAOA-Lévy), to improve efficiency and accuracy in multilevel thresholding. …”
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Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

“…Among the available methods, partial transmit sequence (PTS) is an efficient PAPR reduction method but can be computationally expensive while deter-mining optimal phase factors (OPFs). Therefore, an optimization algorithm, namely, the improved salp swarm optimization algorithm (ISSA), is incorpo-rated with the PTS to reduce the PAPR of the OFDM signals with limited com-putational cost. …”
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Healthcare Prediction Using Novel Machine Learning Methods and Metaheuristic Algorithm by Yazdan Ashgevari, Behrouz Alefy, Faranak Kazemi

“…Four models ETSA, ETCH, SVSA, and SVCH were developed in this study by integrating the ETC and SVC models with two optimization algorithms the CHS and SAO. Upon analyzing the performance of these models, it was found that the ETSA model had a high precision of 0.806 in normal conditions.…”
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Kinematic Constrained RRT Algorithm with Post Waypoint Shift for the Shortest Path Planning of Wheeled Mobile Robots by Sisi Liu, Zhan Zhao, Jun Wei, Qianqian Zhou

“…Once the distance between the new node and the target is within a certain threshold, the tree growth stops and a target connection based on minimum turning radius arc is proposed to generate an initial complete random path. The most significant difference from traditional RRT-based methods is that the proposed method optimizes the path based on Dubins curves through a post waypoint shift after a random path is generated, rather than through parent node selection and rewiring during the exploring tree growth. …”
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An Improved LEACH Protocol for Optimizing Cluster Head Selection and In-cluster Selection by SHIBing, GAOZelin, SUNYueping, HUANJuan, SUNTao

“…This protocol initially employs the root mean square (RMS) of distance within the energy consumption model to determine the optimal number of cluster heads. …”
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Load demand forecasting in air conditioning a rotor Hopfield neural network approach optimized by a new optimization algorithm by Mingguang Liu, Weibo Zhao, Ying Zhou, Mahdiyeh Eslami

“…The RHNN/FO-SOA method may contribute to improve energy performance and reduce costs in air conditioners, shown by the findings.…”
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Optimization of air conditioning mechanical ventilation using simulated annealing for enhanced energy efficiency and cost reduction by Enio Pedone Bandarra Filho, Gleyzer Martins, Muhammad Bilal Riaz, Sardar Muhammad Bilal, Oscar Saul Hernandez Mendonza

“…The methodology integrates principles of fluid mechanics with computational modeling to perform mass and pressure balances, combined with a simulated annealing algorithm for system optimization. The results demonstrate notable reductions in energy consumption, installation costs, and root mean square deviation of airflow rates from design targets. …”
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Development of an Improved KOA Algorithm for Solving Task Allocation in Hilly Orchards With Weeding Robots by Xiaolin Xie, Hang Jin, Heng Wang, Man Xu, Cheng Zhang, Xin Jin, Zhihong Zhang

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An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem by Tao Zhang, Tiesong Hu, Yue Zheng, Xuning Guo

“…An improved particle swarm optimization (PSO) algorithm is proposed for solving bilevel multiobjective programming problem (BLMPP). …”
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A solution to the Single-School school bus routing problem considering accessibility and economy by Zizhan Jiang, Jiying Wang, Siyuan Huang, Hua Daniel Xu

“…A well-designed SBRP strategy can reduce the operating costs of the school bus system, improve accessibility, and ensure timely arrival for teachers and students. …”
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Simultaneous Optimal Allocation of EVCSs and RESs Using an Improved Genetic Method by Majid Farjamipur, Hossein Lotfi, Mohammad Hassan Nikkhah

“…In this research, the improved nondominant sorting genetic algorithm is proposed to solve the problem, and the results of the proposed method are also compared with the conventional genetic and particle swarm optimization algorithms. …”
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An effective parameter estimation on thermoelectric devices for power generation based on multiverse optimization algorithm by Luis Fernando Grisales-Noreña, Vanessa Botero-Gómez, Rubén Iván Bolaños, Faustino Moreno-Gamboa, Daniel Sanin-Villa

“…These results improve over those obtained by the Ant Lion Optimizer, which reported a minimum root mean square error of 0.001804 and a root mean square error of 0.001896 on average with a standard deviation of 3.788%.Additionally, the study highlights the efficiency of the Multiverse Optimization Algorithm in processing time, with an average execution time of 223.65 seconds. …”
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Toward improving precision and complexity of transformer-based cost-sensitive learning models for plant disease detection by Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Oscal Tzyh-Chiang Chen, Oscal Tzyh-Chiang Chen

“…Such an integration acted as regular convolutional layers that subsequently substituted for the original layers to cut computational costs. Furthermore, we adopted the SIoU loss function, a modified version of CIoU, applied to the YOLOv8s model, demonstrating a substantial improvement in accuracy. …”
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Optimisation of decision making for construction projects of assembly buildings based on improved PSO algorithm by Peng Wang

“…The improved particle swarm algorithm converges to an optimal solution of –19.208 within 20 iterations on the Holder function, with an optimal domain of [8.055, –9.665]. …”
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Efficiency management of engineering projects based on particle swarm multi objective optimization algorithm by Xiu Luo, Zhouxin Yi

“…This results indicated that the particle swarm optimization algorithm could provide efficient, cost-effective, and high-quality optimization solutions for engineering project management. …”
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Optimizing Energy and Cost Performance in Residential Buildings: A Multi-Objective Approach Applied to the City of Patras, Greece by Dionyssis Makris, Anastasia Antzoulatou, Alexandros Romaios, Sonia Malefaki, John A. Paravantis, Athanassios Giannadakis, Giouli Mihalakakou

“…The results confirmed the algorithm’s robustness in producing technically feasible and non-dominated solutions, while also highlighting the sensitivity of optimization outcomes to hyperparameter tuning. …”
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