Improved security for IoT-based remote healthcare systems using deep learning with jellyfish search optimization algorithm by Faris Kateb, Mahmoud Ragab, Felwa Abukhodair, Omar Ahmed Abdulkader, Louai A. Maghrabi, Sami Saeed Binyamin, Mohammed Khaled Al-Hanawi

“…The bacterial foraging optimization algorithm (BFOA) method is used for feature extraction. …”
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Bio-Inspired Multiobjective Optimization for Designing Content Distribution Networks by Gerardo Goñi, Sergio Nesmachnow, Diego Rossit, Pedro Moreno-Bernal, Andrei Tchernykh

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A computation offloading scheme for energy consumption optimization in Internet of vehicles by Wenxuan GAO, Xinjie YANG

“…In Internet of vehicles (IoV), vehicle-oriented applications are generally computation-intensive and latency-sensitive.Introducing idle computing resources from mobile vehicles as a supplement to network computing power can effectively alleviate the load pressure on edge servers.The problem of task allocation for edge computation offloading in the context of IoV environment were researched.By fully leveraging the combined computing resources of roadside units (RSU), user vehicles, and mobile vehicles within the RSU service range, a computation offloading strategy based on the sparrow search algorithm was proposed and referred to as sparrow search based computation offloading scheme (S²COS), aiming to optimize the overall system energy consumption.In addition, this strategy fully taked into account practical network issues such as service time constraints caused by vehicle mobility and the potential occurrence of computation node failures.The simulation results demonstrate that S²COS can meet the latency requirements for computation-intensive and latency-sensitive tasks, while significantly reducing system energy consumption.…”
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3D Deployment Optimization of Wireless Sensor Networks for Heterogeneous Functional Nodes by Zean Lu, Chengqun Wang, Peng Wang, Weiqiang Xu

“…The algorithm is compared with the original SBOA, Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Northern Goshawk Optimization (NGO). …”
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Autonomous Decision-Making for Air Gaming Based on Position Weight-Based Particle Swarm Optimization Algorithm by Anqi Xu, Hui Li, Yun Hong, Guoji Liu

“…To verify the effectiveness of the optimization, a 6v6 aircraft gaming simulation example is provided for comparison, and the experimental results show that the convergence speed of the optimized PW-PSO algorithm is 56.34% higher than that of the traditional PSO; therefore, the algorithm can improve the speed of decision-making while meeting the performance requirements.…”
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Energy efficient optimal sink position selection algorithm for multi-sink wireless sensor networks by TANG Wei, GUO Wei

“…In combination with the energy efficient routing algorithm,the optimal sink position selection problem was studied,which aimed to minimize the overall network energy consumption.When the candidate set of sink positions is finite,the problem is shown to be an integer linear programming problem,when the candidate set is the whole space,the problem is shown to be a nonlinear programming problem.Due to the NP-completeness of the problems,several heuristic algorithms were designed accordingly.The proposed algorithms were examined by extensive simulation experiments,the results show that the performances of presented algorithms are close to the optimality.…”
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Research on a stable clustering algorithm based on the optimal connectivity power for wireless sensor networks by LI Fang-min1, LIU Xin-hua1, KUANG Hai-lan1, FANG Yi-lin1

“…In realistic environment, the actual layout of nodes is easy to make network separated and nodes are always densely deployed in hot spots like the site of an accident or disaster where the competition intense was very high.A stable clustering algorithm based on the optimal connectivity power for wireless sensor networks was proposed.The algorithm makes use of the alterable power control technology to raise the channel utilization ratio and network throughput based on the optimal number of neighbors, and realizes the stable connectivity and clustering of network.The algorithm simplifies the topology of network so that prolong the network lifetime at the best.The simulation results show that the algorithm maintains the connectivity and stability of network effectively, and has good auto-adapted ability to environment and obvious effects in the promotion of whole performance of network.…”
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An Optimized Dynamic Scene Change Detection Algorithm for H.264/AVC Encoded Video Sequences by Giorgio Rascioni, Susanna Spinsante, Ennio Gambi

“…This paper deals with the design and performance evaluation of a dynamic scene change detector optimized for H.264/AVC encoded video sequences. The detector is based on a dynamic threshold that adaptively tracks different features of the video sequence, to increase the whole scheme accuracy in correctly locating true scene changes. …”
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Simulation of Natural Gas Pipeline Networks Based on Roughness Optimization Algorithm and Global Mesh Refinement by Yi Yang

“…ABSTRACT Natural gas pipeline network simulation technology is the fundamental technology of system capacity analysis, pipeline design, operation planning and optimization as well as emergency decision‐making for the whole life cycle of a given pipeline network system. …”
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Heat transfer and simulated coronary circulation system optimization algorithms for real power loss reduction by Kanagasabai L.

“…In this paper, the heat transfer optimization (HTO) algorithm and simulated coronary circulation system (SCCS) optimization algorithm has been designed for Real power loss reduction. …”
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A Chemistry-Based Optimization Algorithm for Quality of Service-Aware Multi-Cloud Service Compositions by Mona Aldakheel, Heba Kurdi

“…These results validate the proposed approach’s effectiveness in optimizing service composition while minimizing computational overhead in multi-cloud environments.…”
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Real-Time Drilling Performance Optimization Using Automated Penetration Rate Algorithms with Vibration Control by Dan Sui

“…Automation has transformed process optimization across industries by enhancing efficiency, safety, and reliability while minimizing human intervention. …”
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Optimizing wireless sensor network topology with node load consideration by Ruizhi Chen

“…The K-means clustering algorithm partitions nodes by minimizing the within-cluster variance, while the firefly algorithm is an optimization algorithm based on swarm intelligence that simulates the flashing interaction between fireflies to guide the search process. …”
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DGA-ACO: Enhanced Dynamic Genetic Algorithm—Ant Colony Optimization Path Planning for Agribots by Zhenpeng Zhang, Pengyu Li, Shanglei Chai, Yukang Cui, Yibin Tian

“…A multi-objective fitness function simultaneously optimizes path length, energy efficiency, and safety metrics, while genetic operators prevent algorithmic stagnation. …”
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Optimizing stochastic multi-project scheduling with a simulation integrated multi-objective genetic algorithm by Mudassar Rauf, Muhammad Imran, Jabir Mumtaz, Saima Javed

“…The effectiveness of the proposed SIHMO-GA is evaluated through a real-world case study by comparing it with simulation-optimization approaches, namely the multi-objective genetic algorithm (MOGA) and goal attainment programming. …”
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Spatiotemporally Combined Dimensionality Reduction Algorithm for Optimizing Long-term Operation of Multi-reservoir Systems by CHEN Jia, ZHANG Hanjun, XU Nan

“…To alleviate the “curse of dimensionality” and improve the solution efficiency while ensuring the quality of solutions in optimizing the operation of multi-reservoir systems,this paper proposes a spatiotemporally combined dimensionality reduction algorithm which integrates and improves the dynamic programming with successive approximation (DPSA) and the progressive optimality algorithm (POA).First,a chain-based successive approximation strategy is proposed to expand the DPSA's optimization mode from “single reservoir alternation” to “cascade reservoir chain alternation”,which makes up for the DPSA's shortcomings in dealing with the hydraulic coupling relationships among cascade reservoirs.Then,a dynamic variable decoupling strategy and perturbation mechanism are proposed to deal with the POA's blind search problem and dimensionality problem.Finally,the two improved algorithms are combined,in which the improved POA is applied to solving the optimization problems of cascade reservoir chains under the framework of the improved DPSA.The power generation operation problem of the cascade reservoirs in the Yuan River Basin of Hunan Province and the classical ten-reservoir problem are utilized to test the performance of the proposed algorithm.The proposed algorithm outperforms seven existing alternatives in terms of solution quality and efficiency.The results indicate that the proposed algorithm can effectively alleviate the “curse of dimensionality” in optimizing the operation of multi-reservoir systems,improve the efficiency while ensuring the quality of solutions and has potential to be applied to optimizing the operation of complex large-scale multi-reservoir systems.…”
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An analysis of unconventional grid sizes for wind farm layout optimization using a genetic algorithm by Mohandes Mohamed, Khan Salman A., Rehman Shafiqur, Al-Shaikhi Ali, Iqbal Kashif

“…Due to the sheer complexity of the problem, evolutionary and swarm intelligence algorithms have been employed for wind farm layout optimization. …”
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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…While numerous algorithms exist for protein-ligand docking, achieving an optimal balance between accuracy and computational speed remains challenging. …”
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QELPS Algorithm: A Novel Dynamic Optimization Technology for Quantum Circuits Scheduling Engineering Problems by Zuoqiang Du, Xingjie Li, Hui Li

“…We propose a collaborative optimization framework that integrates the Quantum Exchange Lock Parallel Scheduler (QELPS) with the Full-level Joint Optimization SWAP Algorithm (FJOSA). …”
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Learning-Driven Algorithm With Dual Evolution Patterns for Solving Large-Scale Multiobjective Optimization Problems by Mingshuo Song, Wei Song, Khin Wee Lai

“…Recently, a series of evolutionary algorithms have been proposed to enhance the search efficiency when handling large-scale multiobjective optimization problems (LSMOPs). …”
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