Quantum Approximate Optimization Algorithm for the Max-Cut Problem: JavaScript Programming Language Implementation by Dmytro Sapozhnyk

“…The Max-Cut issue, which involves partitioning the vertices of a graph into two subsets such that the number of edges between the subsets is maximized, is a well-known NP-hard difficulty with numerous practical applications, including network design and resource allocation. The implementation of QAOA in JavaScript is a significant step towards integrating quantum computing with modern web technologies, thus broadening access to quantum algorithms among software developers. …”
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A Deep Q-Learning Algorithm With Guaranteed Convergence for Distributed and Uncoordinated Operation of Cognitive Radios by Ankita Tondwalkar, Andres Kwasinski

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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…Abstract Context Understanding protein-ligand interactions is fundamental to drug design, where optimizing docking parameter selection can potentially enhance computational efficiency and resource allocation in virtual screening. While numerous algorithms exist for protein-ligand docking, achieving an optimal balance between accuracy and computational speed remains challenging. …”
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Enhancing Youbike Redistribution System: A Study on Station Recommendation Using a Genetic Algorithm by Yang-Chou Juan, Yi-Chung Chen, Wei-Ting Chen, Chieh Yang, Chia-Tzu Liu, Yi-Ci Hou, Yi-Hsuan Tsai

“…This study proposes a novel approach to optimize YouBike allocation under resource constraints. We first used K-means clustering to group stations with similar rental profiles, reducing the number of models needed. …”
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PERFORMANCE ANALYSIS OF TASK SCHEDULING USING HYBRID GENETIC MODIFIED WHALE OPTIMIZATION ALGORITHM IN CLOUD COMPUTING by S. Kavitha, G. Paramasivam

“…In this paper, the Hybrid Genetic Modified Whale optimization algorithm which is a combined Genetic and Modified Whale optimization algorithm to analyze the performance of the cloud computing system such as task completion time, execution cost, speedup, and efficiency with proper allocation and sharing of resources The performance of the proposed algorithm is compared with Genetic algorithm and Whale optimization algorithm. …”
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Optimization of artificial intelligence in localized big data real-time query processing task scheduling algorithm by Maojin Sun, Luyi Sun

“…However, in the process of big data processing, the allocation of information resources is often unreasonable, leading to a decrease in efficiency. …”
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A Two-Stage Bin Packing Algorithm for Minimizing Machines and Operators in Cyclic Production Systems by Yossi Hadad, Baruch Keren

“…The outcomes demonstrate the effectiveness of the proposed algorithm in optimizing resource utilization by reducing the number of machines and operators required. …”
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Dynamic multi-criteria scheduling algorithm for smart home tasks in fog-cloud IoT systems by Ruchika Bhakhar, Rajender Singh Chhillar

“…DMCS dynamically allocates tasks based on criteria such as computational complexity, urgency, and data size, ensuring that time-sensitive tasks are processed swiftly on fog nodes while resource-intensive computations are handled by cloud data centers. …”
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Enhancing Cloud Task Scheduling With a Robust Security Approach and Optimized Hybrid POA by S. V. Aswin Kumer, N. Prabakaran, E. Mohan, Balaji Natarajan, G. Sambasivam, Vaibhav Bhushan Tyagi

“…The study evaluates the proposed algorithm’s performance in terms of the make span, resource utilization, cost, response time, throughput, latency, execution time, speed, and bandwidth utilization. …”
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The use of artificial neural network algorithms to enhance tourism economic efficiency under information and communication technology by Yun Tian, Xiaojie Tang

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Two-stage iterative data transmission scheduling algorithm for satellite Internet integrating communication and remote sensing by LI Hai, LI Yongjun, ZHANG Taijiang, LI Yu, ZHAO Shanghong, WANG Jie, HAN Yue

“…In the first stage, delay sensitive data transmission tasks were scheduled using dynamic neighborhood search algorithms. In the second stage, a greedy adaptive large neighborhood search algorithm was proposed to allocate data transmission resources for delay tolerant data transmission tasks. …”
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Fuzzy logic, genetic algorithms, and artificial neural networks applied to cognitive radio networks: A review by Ahmed Alkhayyat, Firas Abedi, Ashish Bagwari, Pooja Joshi, Haider Mahmood Jawad, Sarmad Nozad Mahmood, Yousif K Yousif

“…The cognitive radio works in tandem with artificial intelligence and artificial intelligence methodologies to provide a flexible and intelligent allocation for continuous production cycles. The purpose is to provide a single source of information in the form of a survey research to enable academics better understand how artificial intelligence methodologies, such as fuzzy logics, genetic algorithms, and artificial neural networks, are used to various cognitive radio systems. …”
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A Review of Robot Fleet Management by Paulo H. C. Morais, Kelen C. T. Vivaldini, Edilson R. R. Kato, Roberto S. Inoue

“…Challenges, such as dynamic interaction management and scalability, were examined, emphasizing the practical validation of algorithms and the integration of heterogeneous fleets. …”
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A personalized recommendation algorithm for English exercises incorporating fuzzy cognitive models and multiple attention mechanisms by Yixuan Zhang, Yanyi Wang

“…Abstract In the era of digital education, the rapid growth and disordered distribution of learning resources present new challenges for online learning. …”
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Effect of the Sampling of a Dataset in the Hyperparameter Optimization Phase over the Efficiency of a Machine Learning Algorithm by Noemí DeCastro-García, Ángel Luis Muñoz Castañeda, David Escudero García, Miguel V. Carriegos

“…It is a laborious task that usually requires deep knowledge of the hyperparameter optimizations methods and the Machine Learning algorithms. Although there exist several automatic optimization techniques, these usually take significant resources, increasing the dynamic complexity in order to obtain a great accuracy. …”
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Improved genetic algorithm based on Shapley value for a virtual machine scheduling model in cloud computing by Lili Chen, Lili Chen, Yuxia Niu

“…IntroductionIn cloud computing, a common idea to reduce operation costs and improve service quality is to study task scheduling algorithms.MethodsTo better allocate virtual machine resources, a virtual machine resource scheduling algorithm, Shapley value method–genetic algorithm (SVM-GA) is proposed. …”
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An optimized method for short-term load forecasting based on feature fusion and ConvLSTM-3D neural network by Xiaofeng Yang, Shousheng Zhao, Kangyi Li, Wenjin Chen, Si Zhang, Jingwei Chen

“…As renewable energy continues to penetrate modern power systems, accurate short-term load forecasting is crucial for optimizing power generation resource allocation and reducing operational costs. …”
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Rapid Beam Forming in Smart Antennas Using Smart-Fractal Concepts Employing Combinational Approach Algorithms by Mounissamy Levy, Sumanta Bose, D. Sriram Kumar, Anh Van Dinh

“…The important properties of fractal arrays are frequency independent multiband characteristics, schemes for realizing low side lobe designs, systematic approaches to thinning, and the ability to develop rapid beam forming algorithms. In this paper, an attempt has been made to apply assignment of usage time and location tag algorithm for smart antennas combined with the fractal concepts to reduce the computational complexity and enhance resource allocation for rapid beam forming algorithms. …”
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Optimizing a Machine Learning Algorithm by a Novel Metaheuristic Approach: A Case Study in Forecasting by Bahadır Gülsün, Muhammed Resul Aydin

“…Accurate sales forecasting is essential for optimizing resource allocation, managing inventory, and maximizing profit in competitive markets. …”
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A Tabu Search-Based Algorithm for Airport Gate Assignment: A Case Study in Kunming, China by Jun Bi, Zhen Wu, Lei Wang, Dongfan Xie, Xiaomei Zhao

“…A tabu search-based algorithm is designed to solve the problem. In the process of algorithm design, an effective initial solution is obtained. …”
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