Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform. by Nhu-Ngoc Dao, Minho Park, Joongheon Kim, Sungrae Cho

“…The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. …”
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Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor–Recipient Matching by Nahed Alowidi, Razan Ali, Munera Sadaqah, Fatmah M. A. Naemi

“…(1) Background: Globally, the kidney donor shortage has made the allocation process critical for patients awaiting a kidney transplant. …”
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Multi-dimensional flux balance analysis to optimized resources and energy efficiency in MEC aided 5G networks by Rachit Patel, Rajeev Arya

“…In comparison to (1) Resource allocations using Q learning with considering parameter throughput-RA(QL-Munkres-TH), (2) Resource allocations using Q learning with considering parameter distance-RA(QL-Munkres-Dist), and (3) Resource allocation with considering maximum power-RA(Max-Power), the suggested method reduces energy consumption by 83.26%, 86.01%, and 88.34%, respectively. …”
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Algorithms to Identify Copied and Manipulated Spectrum Occupancy Data in Cognitive Radio Networks by Joseph Tolley, Carl B. Dietrich

“…Spectrum Access Systems (SASs) and similar systems coordinate access to shared radio frequency bands to efficiently allocate the use of spectrum between users in a locality. …”
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An Integrated Implementation Framework for Warehouse 4.0 Based on Inbound and Outbound Operations by Jizhuang Hui, Shaowei Zhi, Weichen Liu, Changhao Chu, Fuqiang Zhang

“…First, for inbound processes, an algorithm-driven storage allocation model is proposed to solve stacker crane scheduling problems. …”
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Network media streaming offloading algorithm based on QoE in mobile edge network by Zaijian WANG, Hao CHENG

“…Aiming at the problems of high-latency, high energy consumption, high bandwidth, and poor quality of experience (QoE) caused by emerging network media streaming business in mobile edge computing, a computing offloading algorithm based on QoE feedback configuration was proposed.Firstly, both preprocessing and priority were comprehensively considered to maximize network resource utilization.Meanwhile, different weights were assigned to the computation tasks for establishing a resource allocation relationship.Secondly, after comprehensively taking into account deadline, computing resource, power and bandwidth constraint, an QoE model was established where the optimization objective was the weighted sum of task delay, energy consumption and precision, and the method of Lagrange multipliers was utilized to solve the established model.Simulation results indicate that, compared with the deep reinforcement learning-based online offloading algorithm, the proposed algorithm can effectively optimize the resource allocation and better improve the QoE.…”
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New Courteous Algorithm for Uplink Scheduling in LTE-Advanced and 5G Networks by Chafika Tata, Nassima Fellag, Michel Kadoch

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Parallel CUDA-Based Optimization of the Intersection Calculation Process in the Greiner–Hormann Algorithm by Jiwei Zuo, Junfu Fan, Kuan Li, Qingyun Liu, Yuke Zhou, Yi Zhang

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Clustering of High School Students Academic Scores Using K-Means Algorithm by Chairunisa Azzahra, Sriani Sriani

“…Additionally, clustering outcomes provide valuable insights for refining teaching strategies, allocating resources more effectively, and personalizing learning approaches to suit each student's needs. …”
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Network media streaming offloading algorithm based on QoE in mobile edge network by Zaijian WANG, Hao CHENG

“…Aiming at the problems of high-latency, high energy consumption, high bandwidth, and poor quality of experience (QoE) caused by emerging network media streaming business in mobile edge computing, a computing offloading algorithm based on QoE feedback configuration was proposed.Firstly, both preprocessing and priority were comprehensively considered to maximize network resource utilization.Meanwhile, different weights were assigned to the computation tasks for establishing a resource allocation relationship.Secondly, after comprehensively taking into account deadline, computing resource, power and bandwidth constraint, an QoE model was established where the optimization objective was the weighted sum of task delay, energy consumption and precision, and the method of Lagrange multipliers was utilized to solve the established model.Simulation results indicate that, compared with the deep reinforcement learning-based online offloading algorithm, the proposed algorithm can effectively optimize the resource allocation and better improve the QoE.…”
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Optimizing energy and latency in edge computing through a Boltzmann driven Bayesian framework for adaptive resource scheduling by Dinesh Sahu, Nidhi, Rajnish Chaturvedi, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Idrees Alsolbi

“…Abstract This paper presents a new approach based on Boltzmann Distribution and Bayesian Optimization to solve the energy-efficient resource allocation in edge computing. It employs Bayesian Optimization to optimize the parameters iteratively for the minimum energy consumption and latency. …”
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Research on E-Commerce Inventory Sales Forecasting Model Based on ARIMA and LSTM Algorithm by Chenyang Wang, Junsheng Wang

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Efficiency management of engineering projects based on particle swarm multi objective optimization algorithm by Xiu Luo, Zhouxin Yi

“…In addition, in medical resource allocation, multi-objective particle swarm optimization algorithm can optimize the resource allocation plan, balancing fairness and efficiency. …”
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Economic operation analysis of the power grid combining communication network and distributed optimization algorithm by Yi Zhifei

“…It is necessary to strengthen communication and resource allocation in practical applications.…”
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A Constrained Multi-Objective Optimization Algorithm with a Population State Discrimination Model by Shaoyu Zhao, Heming Jia, Yongchao Li, Qian Shi

“…A simple yet effective resource allocation model is incorporated to address the potential computational resource waste associated with dual populations, enhancing the resource utilization. …”
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A GD-PSO Algorithm for Smart Transportation Supply Chain ABS Portfolio Optimization by Yingjia Sun, Hongfeng Ren

“…In this article, a penalty function based on graph density (GD) was introduced to the particle swarm optimization algorithm (PSO), and a GD-PSO algorithm was proposed. …”
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Multi-objective optimal probabilistic planning in distribution systems considering load growth by Ayat Saleh

“…This paper presents the operation of distribution networks with dispatch able mix of different types of distributed energy resources (DERs) units considering load growth up to planning period based on Multi Variant Differential Evolution algorithm (MVDE). …”
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Algorithms for Load Balancing in Next-Generation Mobile Networks: A Systematic Literature Review by Juan Ochoa-Aldeán, Carlos Silva-Cárdenas, Renato Torres, Jorge Ivan Gonzalez, Sergio Fortes

“…The need for enhanced radio resource allocation schemes, improved user mobility and increased throughput, driven by a rising demand for data, has necessitated the development of diverse algorithms that optimize output values based on varied input parameters. …”
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Optimizing Crop Yield Prediction: An In-Depth Analysis of Outlier Detection Algorithms on Davangere Region by C. S. Anu, C. R. Nirmala, A. Bhowmik, A. Johnson Santhosh

“…Crop yield prediction is a critical aspect of agricultural planning and resource allocation, with outlier detection algorithms playing a vital role in refining the accuracy of predictive models. …”
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SMOTE algorithm optimization and application in corporate credit risk prediction with diversification strategy consideration by Han Wei

“…On one hand, this study focuses on optimizing the Synthetic Minority Over-Sampling Technique (SMOTE) algorithm for corporate credit risk prediction, thereby enhancing financial institutions’ risk management capabilities. …”
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