Enhancing network lifetime in WSNs through coot algorithm-based energy management model by Namita Shinde, Dr. Vinod H․ Patil

“…To improve the performance of Wireless Sensor Networks (WSN), this study offers a novel energy-efficient clustering and routing technique based on the Coot Optimization Algorithm (COA). This addresses issues such as high energy consumption, communication delays, and security.To ensure energy savings and network reliability, the fitness function evaluates cluster heads and best routes based on constraints.COOT outperforms other Metaheuristics Algorithms like Butterfly Optimization Algorithm, Genetic Algorithm, Tunicate Swarm Gray Wolf Optimization Algorithm, and Bird Swarm Algorithm in simulation with performance measurements and enhancing network functionality and protection.Key methodology points include: • Proposed a multiple constraints clustering and routing technique using COAto solve the most crucial issues that arise in WSNs. • Integrated an advanced fitness function that determines cluster head selection, and the routing path based on residual energy, delay, security, trust, distance, and link quality so that energy load is evenly distributed and credible data flow is maintained across the network and made Innovative and Effective Solution. • Proven Results Demonstrated superior network performance, achieving the lowest delay, highest network lifetime (3571 rounds) and enhanced security (0.8) and trust (0.6) compared to existing algorithms with less energy consumption, making it the most suitable solution for WSN performance improvement.…”
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Aerial RIS Aided NOMA Networks with Optimized Secrecy Metrics Performance by F. Titel, M. Belattar, M. Lashab, R. Abd-Alhameed

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Optimizing Solid Oxide Fuel Cell Performance Using Advanced Meta-Heuristic Algorithms by Siva Ram Rajeyyagari, Srinivas Nowduri

“…These include the Angle of Attack Optimization (AOA), Particle Swarm Optimization with Grey Wolf Optimizer (PSOGWO), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Moth Flame Optimization (MFO), and Multi-Verse Optimizer (MVO). …”
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A parallel multi-objective genetic algorithm for scheduling scientific workflows in cloud computing by Muhammad Sardaraz, Muhammad Tahir

“…The proposed algorithm is evaluated with benchmark datasets and comparative results with the standard genetic algorithm, particle swarm optimization, and specialized scheduler are presented. …”
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A Comparison of the Black Hole Algorithm Against Conventional Training Strategies for Neural Networks by Péter Veres

“…This study presents a comparative analysis of four training algorithms, Backpropagation, Genetic Algorithm, Black-hole Algorithm, and Particle Swarm Optimization, evaluated across both classification and regression tasks. …”
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Expert-based sustainable investment strategies for SMEs with hybrid molecular fuzzy learning algorithms by Anisah Firli, Dadan Rahadian, Hasan Dinçer, Serhat Yüksel, Deannes Isyuwardhana, Cahyaningsih, Putri Fariska

“…Secondly, selected criteria are evaluated by molecular fuzzy Bayesian networks-based weighting methodology. …”
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Enhancing workflow efficiency with a modified Firefly Algorithm for hybrid cloud edge environments by Deafallah Alsadie, Musleh Alsulami

“…Abstract Efficient scheduling of scientific workflows in hybrid cloud-edge environments is crucial for optimizing resource utilization and minimizing completion time. In this study, we evaluate various scheduling algorithms, emphasizing the Modified Firefly Optimization Algorithm (ModFOA) and comparing it with established methods such as Ant Colony Optimization (ACO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). …”
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Various optimization algorithms for efficient placement and sizing of photovoltaic distributed generations in different networks. by Ahmed A Zaki Diab, Fayza S Mahmoud, Hamdy M Sultan, Abou-Hashema M El-Sayed, Mohamed A Ismeil, Omar Makram Kamel

“…Various optimization techniques, namely Salp Swarm Algorithm (SSA), Marine Predictor Algorithm (MPA), Grey Wolf Optimizer (GWO), Improved Grey Wolf Optimizer (IGWO), and Seagull Optimization Algorithm (SOA), have been applied to achieve optimal allocation and sizing of RDGs in radial distributed systems (RDS). …”
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Machine Learning-Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete by Muhammad Izhar Shah, Shazim Ali Memon, Muhammad Sohaib Khan Niazi, Muhammad Nasir Amin, Fahid Aslam, Muhammad Faisal Javed

“…In this research, multiexpression programming (MEP) has been employed to model the compressive strength, splitting tensile strength, and flexural strength of waste sugarcane bagasse ash (SCBA) concrete. Particle swarm optimization (PSO) algorithm was used to fine-tune the hyperparameter of the proposed MEP. …”
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Application of the Multi-Strategy Improved Walrus Optimization Algorithm in Mobile Robot Path Planning by Yongfu Ke, Limei Shi, Weinan Ji, Peng Luo, Lei Guo

“…It’s capable of significantly improving the overall performance of the algorithm. Evaluating the performance of the proposed algorithm, this paper conducts experiments with three distinct sets of benchmark functions and compares the outcomes against various swarm intelligence algorithms. …”
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Investigation of technoeconomic optimization for sizing renewable energy systems using metaheuristic and hybrid algorithms by Bouafia Mohammed, El Fathi Amine, El Akchioui Nabil

“…This study focuses on optimizing grid-connected Hybrid Renewable Energy Systems (HRES) in Morocco using technoeconomic approaches, including metaheuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimization (GWO) and Artificial Bee Colony (ABC) and hybrid methods combining these latter with Modified Marquardt Gradient Descent (MGD). …”
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Multistep PV power forecasting using deep learning models and the reptile search algorithm by Sameer Al-Dahidi, Hussein Alahmer, Bilal Rinchi, Abdullah Bani-Abdullah, Mohammad Alrbai, Osama Ayadi, Loiy Al-Ghussain

“…Further, RSA was benchmarked against the Whale Optimization Algorithm (WOA), Gray Wolf Optimizer (GWO), and Constrained Particle Swarm Optimization (CPSO), and consistently outperformed all three across all models in both forecasting horizons. …”
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Frequency regulation of two-area thermal and photovoltaic power system via flood algorithm by Serdar Ekinci, Davut Izci, Cebrail Turkeri, Aseel Smerat, Absalom E. Ezugwu, Laith Abualigah

“…These include sea horse optimization, salp swarm algorithm, whale optimization algorithm, shuffled frog-leaping algorithm, and firefly algorithm. …”
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Generic multidimensional economic environmental operation of power systems using equilibrium optimization algorithm by Mohamed T. Mouwafi, Adel A. Abou El-Ela, Amany A. El-Hamoly, Ragab A. El-Sehiemy

“…The numerical results obtained by the proposed EOA are compared with other optimization techniques such as grey wolf optimization, particle swarm optimization (PSO), differential evolution algorithm, and other optimization techniques in the literature. …”
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Unmanned Aerial Vehicles (UAV) Networking Algorithms: Communication, Control, and AI-Based Approaches by Mien L. Trinh, Dung T. Nguyen, Long Q. Dinh, Mui D. Nguyen, De Rosal Ignatius Moses Setiadi, Minh T. Nguyen

“…This paper focuses on algorithms and technologies for unmanned aerial vehicles (UAVs) networking across different fields of applications. …”
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DEVELOPMENT OF HEALTH INSURANCE CLAIM PREDICTION METHOD BASED ON SUPPORT VECTOR MACHINE AND BAT ALGORITHM by Syaiful Anam, Abdi Negara Guci, Fery Widhiatmoko, Mila Kurniawaty, Komang Agus Arta Wijaya

“…BA has a faster convergence rate than other algorithms, for example Particle Swarm Optimization (PSO). …”
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INVERSION OF PARAMETERS FOR COMPOSITE INTERLAYER COHESIVE ZONE MODEL BY USING ARTIFICIAL BEE COLONY ALGORITHM by RAO YuWen, LIN RenBang, YANG YanZhi, YAN Gang

“…Numerical and experimental results have demonstrated that,ABC algorithm has better convergence and optimization ability than genetic（ GA） algorithm and particle swarm optimization（ PSO） algorithm; it has certain anti-noise capability that can optimally obtain the CZM parameters under different levels of measurement noise,and the simulated load-displacement data with the inversely identified parameters match the actual test ones well.…”
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Selection and Prioritization of Test Cases by using Bees Colony by Shahbaa Khaleel, Ragad khaled

“…And that was performed through using Artificial Bees Colony ABC Algorithm in selection of test cases for the software written by C++ language in an automatic way since to enable the corporation which develops the software to save time, effort  and costs that required for testing phase and regression testing activity, which is always evaluated by 50% of the product cost. …”
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Design of an evolutionary model for international trade settlement based on genetic algorithm and fuzzy neural network. by Jiaqing Huang, Yang Liu, Miaomiao Tu, Osama Sohaib

“…Results show that GA-FNN achieves an average classification accuracy of approximately 90% across high, medium, and low risk levels, outperforming traditional methods such as logistic regression, SVM (Support Vector Machine), and other metaheuristics like PSO (Particle Swarm Optimization) and SA (Simulated Algorithm). …”
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Influencing factors of cross screening rate and its intelligent prediction model by Lala ZHAO, Feng XU, Chenlong DUAN, Chenhao GUO, Wei WANG, Haishen JIANG, Jinpeng QIAO

“…The corresponding evaluation indexes EMS and EMA are 3.110×10−4 and 1.353×10−2. …”
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