Improving energy efficiency and network performance in IaaS cloud with virtual machine placement by Jian-kang DONG, Hong-bo WANG, Yang-yang LI, Shi-duan CHENG

“…The existing virtual machine(VM) placement schemes mostly reduce energy consumption by optimizing utilization of physical server or network element.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,a VM placement scheme was proposed to achieve two objectives.One is to minimize the number of activating physical machines and network elements to reduce the energy consumption,and the other is to minimize the maximum link utilization to improve the network performance.This scheme is able to reduce the energy consumption caused by physical servers and network equipment while optimizing the network performance,making a trade off between energy efficiency and network performance.A novel two-stage heuristic algorithm for a solution was designed.Firstly,the hierarchical clustering algorithm based on minimum cut and best fit algorithm was used to optimize energy efficiency,and then,local search algorithm was used to minimize the maximum link utilization.The simulations show that this solution achieves good results.…”
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Improved energy efficiency using meta-heuristic approach for energy harvesting enabled IoT network by Rekha, Ritu Garg

“…In this article, we propose an optimization algorithm, based on meta-heuristic, to enhance the energy efficiency of amplify and forward relay IoT networks. …”
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Solving the Traveling Salesman Problem Based on The Genetic Reactive Bone Route Algorithm whit Ant Colony System by Majid Yousefikhoshbakht, Nasrin Malekzadeh, Mohammad Sedighpour

“…The TSP is considered one of the most well-known combinatorial optimization tasks and researchers have paid so much attention to the TSP for many years. …”
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Improvement of Energy Indicators of Asynchronous Motor under the Conditions of Asymmetric Voltage Supply by Boyko A.A., Besarab A.N., Sokolov Y.A., Shapa L.N.

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Modeling and Optimization of Beam Pumping System Based on Intelligent Computing for Energy Saving by Xiaohua Gu, Taifu Li, Zhiqiang Liao, Liping Yang, Ling Nie

“…It firstly employs the general regression neural network (GRNN) algorithm to obtain the best model of the beam pumping system, and secondly searches the optimal operation parameters with improved strength Pareto evolutionary algorithm (SPEA2). …”
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Improving parking availability prediction in smart cities with IoT and ensemble-based model by Stéphane Cédric Koumetio Tekouabou, El Arbi Abdellaoui Alaoui, Walid Cherif, Hassan Silkan

“…The tests that we carried out on the Birmingham parking data set allowed to reach a Mean Absolute Error (MAE) of 0.06% on average with the algorithm of Bagging Regression (BR). This results have thus improved the best existing performance by over 6.6% while dramatically reducing system complexity.…”
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An optimization method of multiscale storage tank target detection introducing an attention mechanism by Wenjia Sun, Chunchun Hu, Nianxue Luo, Qiansheng Zhao

“…Finally, the EIOU loss function is employed instead of the CIOU loss function in the original model to improve the algorithm’s accuracy and speed. Experimental results show that the optimized model significantly improves the detection effect on small targets compared with the original YOLOv5 model. …”
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Technique on Vehicle Damage Assessment After Collisions Using Optical Radar Technology and Iterative Closest Point Algorithm by Shih-Lin Lin, Yi-Hsuan Chen

“…We apply the Iterative Closest Point (ICP) algorithm and Singular Value Decomposition (SVD) methods, along with a proposed deep learning neural network optimization model, to perform point cloud alignment between the pre-collision and post-collision vehicle models. …”
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Multibranch semantic image segmentation model based on edge optimization and category perception. by Zhuolin Yang, Zhen Cao, Jianfang Cao, Zhiqiang Chen, Cunhe Peng

“…Second, a category perception module is used to learn category feature representations and guide the pixel classification process through an attention mechanism to optimize the resulting segmentation accuracy. Finally, an edge optimization module is used to integrate the edge features into the middle and the deep supervision layers of the network through an adaptive algorithm to enhance its ability to express edge features and optimize the edge segmentation effect. …”
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Preference-based expensive multi-objective optimization without using an ideal point by Peipei Zhao, Liping Wang, Qicang Qiu

“…However, most existing methods rely on the estimated ideal point. …”
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Optimization Path and Design of Intelligent Logistics Management System Based on ROS Robot by Ruijie Wu

“…Therefore, this paper aimed to design an intelligent logistics management system based on ROS robot and proposed to use the A-star algorithm to calculate the shortest path of the robot so as to achieve the optimal path. …”
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Determination of Optimal Parameters of the Ground Filling During the Laying of Power Cable Lines by M. E. Vysotski

“…Otherwise, the use of special backfills becomes impractical. To solve the optimization problem, a genetic algorithm implemented in the MS Excel environment was used. …”
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An SVDD-based post-processing approach for vibration risk assessment of the hydro-turbine-generator in a large hydropower station by Jinliang Zhang, Fengwei Yang, Chao Liang, Yuansheng Zhang, Yongchang Li

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Individualized post‐operative prediction of cochlear implantation outcomes in children with prelingual deafness using functional near‐infrared spectroscopy by Zhe Chen, Xue Zhao, Haotian Liu, Yuyang Wang, Zhikai Zhang, Yuxuan Zhang, Yuhe Liu

“…Both classification and individualized regression models were constructed to predict post‐CI behavioral improvement from fNIRS data using support vector machine (SVM) learning algorithms. …”
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An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things by Mai Alduailij

“…For the feature selection process, the binary grey wolf optimization (BGWO) model is employed to identify and retain the most significant features in the dataset. …”
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INNOVATIVE MECHANISMS FOR IMPLEMENTING STATE ECONOMIC POLICY FOR POST-WAR RECONSTRUCTION OF UKRAINE: QUANTUM TRANSFORMATIONS AS A DRIVER OF DEVELOPMENT by Oleksiy Shkuratov, Liudmila Antonova, Roman Dzyuba

“…The quantum transformation of Ukraine's economy in the conditions of post-war recovery can become an important component of the state investment policy, which will stimulate innovative development and increase the country's competitiveness in the international arena. …”
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Reliability evaluation of dynamic face recognition systems based on improved Fuzzy Dynamic Bayesian Network by Zhiqiang Liu, Wenbo Zhu, Hongzhou Zhang, Shengjin Wang, Lu Fang, Weijun Hong, Hua Shao, Guopeng Wang

“…In this article, we propose a novel evaluation method with True Positive Identification Rate in dynamic and M:N mode and create a novel evaluation model of system reliability with the improved Fuzzy Dynamic Bayesian Network. Subsequently, we infer to solve the fuzzy reliability state probabilities of the six systems with Netica and get two most important factors with the improved fuzzy C-means algorithm. …”
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Numerical Investigation and Optimization of Transpiration Cooling Plate Structures with Combined Particle Diameter by Dan Wang, Yaxin Liu, Xiang Zhang, Mingliang Kong, Hanchao Liu

“…Further optimization with the multi-objective genetic algorithm (MOGA) determines the optimal structural parameters. …”
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Machine-Learning-Algorithm-Assisted Portable Miniaturized NIR Spectrometer for Rapid Evaluation of Wheat Flour Processing Applicability by Yuling Wang, Chen Zhang, Xinhua Li, Longzhu Xing, Mengchao Lv, Hongju He, Leiqing Pan, Xingqi Ou

“…By employing an improved whale optimization algorithm (iWOA) coupled with a successive projections algorithm (SPA), we selected the 20 most informative wavelengths (MIWs) from the full range spectra, allowing the iWOA/SPA-SOA-SVR model to predict SV with correlation coefficient and root-mean-square errors in prediction (R_P and RMSE_P) of 0.9605 and 0.2681 mL. …”
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Research Progress on Machine Learning Prediction of Compressive Strength of Nano-Modified Concrete by Ruyan Fan, Ankang Tian, Yikun Li, Yue Gu, Zhenhua Wei

“…Nano-modified concrete has attracted wide attention due to its improved mechanical properties. Among them, compressive strength is the most critical indicator. …”
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