Optimization Planning Techniques with Meta-Heuristic Algorithms in IoT: Performance and QoS Evaluation by İsa Avcı, Murat Koca

“…This work organizes its most innovative contribution around optimization scheduling techniques, which are based on three meta-heuristic algorithms. These algorithms include the particle swarm algorithm, the genetic algorithm, and the ant colony algorithm. …”
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Artificial Bee Colony and Newton Algorithm for Forward Position Solution of Parallel Mechanism by Ping Li, Siyang Peng, Linxian Che, Li Du, Junkun Hong

“…Furthermore， comparative tests to solve these examples are carried out with HABC-Newton， ABC， DE and particle swarm optimization algorithms， and the numerical experiments indicate that HABC-Newton algorithm has better performance than compared algorithms in terms of the accuracy， robustness and computational efficiency.…”
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Intrusion detection algorithm of wireless network based on network traffic anomaly analysis by Xiangqian Nie, Jiao Xing, Qimeng Li, Fan Xiao

“…These features are analyzed by an intrusion detection module combining particle swarm optimization and support vector machine algorithms. …”
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Research on resource allocation algorithm of centralized and distributed Q-learning in machine communication by Yunhe YU, Jun SUN

“…Under the premise of ensuring partial machine type communication device (MTCD)’s quality of service (QoS) requirements, the resource allocation problem was studied with the goal of maximizing system throughput in the massive machine type communication (mMTC) scenario.Two resource allocation algorithms based on Q-learning were proposed: centralized Q-learning algorithm (team-Q) and distributed Q-learning algorithm (dis-Q).Firstly, taking into account MTCD’s geographic location and multi-level QoS requirements, a clustering algorithm based on cosine similarity (CS) was designed.In the clustering algorithm, multi-dimensional vectors that represent MTCD and data aggregator (DA) were constructed, and MTCDs can be grouped according to the CS value between multi-dimensional vectors.Then in the MTC network, the team-Q learning algorithm and dis-Q learning algorithm were used to allocate resource blocks and power for the MTCD.In terms of throughput performance, team-Q and dis-Q algorithms have an average increase of 16% and 23% compared to the dynamic resource allocation algorithm and the greedy algorithm, respectively.In terms of complexity performance, the dis-Q algorithm is only 25% of team-Q algorithm and even below, the convergence speed is increased by nearly 40%.…”
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DAG Based Multipath Routing Algorithm for Load Balancing in Machine-to-Machine Networks by Liang Liu, Tao Zhang, Jun Zhang

“…In addition, our algorithm is a polynomial time complexity algorithm with nodes and links number of the entire network.…”
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Design and Control for Piezoelectric Energy Harvester Based on a Heuristic Optimization Algorithms by Habeeb Jaber Nekad, Diyah Kammel Shary, Oday Alahmad

“…The parameters of the second controller will be optimized by using various heuristic algorithms. (Ant Colony Optimization (ACO), Modified Camel Traveling Algorithm (MCTA), and Particle Swarm Optimization (PSO)). …”
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Fog node intrusion detection and response based on SVMIF and INSGA-II algorithm by Zhuojun Luo

“…Additionally, modified particle swarm optimization was employed to optimize the model's parameters. …”
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Application of multi-sensor fusion localization algorithm based on recurrent neural networks by Zexia Huang, Guoyang Ye, Pu Yang, Wanshun Yu

“…The method also outperforms state-of-the-art algorithms, including Particle Filter (PF) and Graph SLAM, in both accuracy and computational efficiency, achieving an average runtime of 30.1 ms per frame, suitable for real-time applications. …”
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UAV Path Planning under Dynamic Threats Using an Improved PSO Algorithm by Jong-Jin Shin, Hyochoong Bang

“…In addition, terrain masking, nonisotropic radar cross section (RCS), and dynamic constraints of UAV are considered to determine the cost of the path. An improved particle swarm optimization (PSO) algorithm is proposed for finding an optimal path. …”
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Synthesis of Thinned Concentric Circular Antenna Arrays Using Modified TLBO Algorithm by Zailei Luo, Xueming He, Xuedong Chen, Xin Luo, Xiaoqing Li

“…Numerical results clearly show the superiority of MTLBO algorithm in finding optimum solutions compared to particle swarm optimization algorithm and firefly algorithm.…”
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Optimal Energy Management of Microgrids using Quantum Teaching Learning Based Algorithm by Zahra Esmaeili, Seyed Hamid Hosseini

“…In this paper, a robust frame associated with a quantum version of the Teaching-Learning-Based Optimization (quantum TLBO) algorithm is proposed for the first time for the microgrid optimal energy management problem. …”
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Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System by Chen Wang, Lincoln C. Wood, Heng Li, Zhenye Aw, Abolfazl Keshavarzsaleh

“…However, the existing fire evacuation routing models using various algorithm such as ant colony optimization or particle swarm optimization can neither properly interpret the delay caused by congestion during evacuation nor determine the best layout of emergency exit guidance signs; thus bee colony optimization is expected to solve the problem. …”
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Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands by Radek Halfar, Jiří Damborský, Sérgio M. Marques, Jan Martinovič

“…Here we present Moldina (Multiple-Ligand Molecular Docking over AutoDock Vina), a new algorithm built upon AutoDock Vina. Through comprehensive testing against AutoDock Vina, the algorithm exhibited comparable accuracy in predicting ligand binding conformations while significantly reducing the computational time up to several hundred times. …”
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Meaning in the Algorithmic Museum: Towards a Dialectical Modelling Nexus of Virtual Curation by Huining Guan, Pengbo Chen

“…The rise of algorithm-driven virtual museums presents a philosophical challenge for how cultural meaning is constructed and critiqued in digital curation. …”
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Estimation Algorithm of Machine Operational Intention by Bayes Filtering with Self-Organizing Map by Satoshi Suzuki, Fumio Harashima

“…We present an intention estimator algorithm that can deal with dynamic change of the environment in a man-machine system and will be able to be utilized for an autarkical human-assisting system. …”
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Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification by Shahad Alkamli, Hala Alshamlan

“…Comparative analysis with Harris Hawks Optimization (HHO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), and Firefly Algorithm (FFA) shows that while NRO delivers competitive performance, it does not consistently outperform all methods across datasets. …”
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Maximum likelihood DOA estimation based on improved ant colony optimization algorithm by JIAO Yameng, LI Wenping, WU Yue, CUI Lin

“…Simulation results show that, compared with ML estimation methods based on particle swarm optimization (PSO) algorithm and ACO algorithm, the convergence speed of the ML-MACO algorithm is 4 times faster than that of the ML-ACO algorithm, the computational load is 1/3 that of the ML-ACO algorithm, the resolution success rate is higher than the ML-PSO algorithm and the ML-ACO algorithm, and the estimation error is less than the ML-PSO algorithm and the ML-ACO algorithm. …”
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Queueing modeling and optimization of hybrid electric vehicle infrastructures using evolutionary algorithms by Shreekant Varshney, Manthan Shah, Bhasuru Abhinaya Srinivas, Mayank Gupta, Kaibalya Prasad Panda

“…The novelty of the proposed research is to formulate the cost optimization problem and demonstrate optimal converging outcomes through an in-depth comparative investigation of multiple evolutionary algorithms, including the particle swarm optimization (PSO), cuckoo search (CS), grey wolf (GW), and honey badger (HB) optimizers. …”
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Commercial Vehicle Ride Comfort Optimization Based on Intelligent Algorithms and Nonlinear Damping by Shuilong He, Keren Chen, Enyong Xu, Wei Wang, Zhansi Jiang

“…By applying the particle swarm optimization (PSO), cuckoo search (CS), dividing rectangles (DIRECT), and genetic algorithm (GA), a set of optimal solutions are obtained. …”
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Collision avoidance method for unmanned ships using a modified APF algorithm by Lianbo Li, Wenhao Wu, Zhengqian Li, Fangjie Wang

“…The Artificial Potential Field (APF) algorithm has been widely used for collision avoidance on unmanned ships. …”
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