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 GOA-based fuzzy PI speed control of PMSM with predictive current regulation. by Taochang Li, Ang Li, Limin Hou

“…Subsequently, the fusion of Cauchy mutation and opposition-based learning, along with modifications to the optimal position, further improves the algorithm's ability to escape local optima. …”
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A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

“…Moreover, we introduce a cross-model method with a genetic algorithm to compute the optimal weights for the RBF-NN model. …”
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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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Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest by X Peng, C Chen, L Yu, X Kong, B Sun

“…The RF_WOA_DBO hybrid model achieved an accuracy of 98.29%, representing a 4.28% improvement over the baseline RF model. …”
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Water Supply Scheduling for Cross-basin Reservoir Groups Based on Improved Scheduling Diagram by ZHAO Siqi, XU Wei, CHEN Si, WANG Sufan, YANG Yi

“…To exploit the scheduling potential of cross-basin reservoir groups by employing runoff information,this paper proposes an improved reservoir scheduling diagram to retain simplicity and intuitiveness.Taking the Xiajiankou,Fengyan,and Nanpeng reservoirs in Banan District of Chongqing as an example,it adopts the POA algorithm to build a joint scheduling model of water diversion and water supply for the cross-basin reservoir groups by a simulation-optimization approach.Meanwhile,three scenarios of the current situation scheduling,optimized scheduling with conventional scheduling diagrams,and optimized scheduling with improved scheduling diagrams are set up to evaluate the water diversion and supply performance of reservoirs and analyze the influence of uncertainty runoff information on the scheduling performance.The results are as follows:① The improved scheduling diagram performs best in the long series scheduling,and it can increase the annual average water supply of the reservoir group by 6.87% and reduce the abandoned water by 87.58% compared with the current situation scheduling;② In a dry year,the method can reduce 486.3×10⁴ m³ of water shortage and increase 477.6×10⁴ m³ of water for power generation based on the current situation scheduling;③ When considering the runoff information uncertainty,the water supply of the improved scheduling diagram is 3.37% lower than the ideal case but is still 5.96% more than the conventional optimization.The results are conducive to making scientific decisions and improving the water supply effect.…”
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Voltage and frequency regulation in wind penetrated deregulated power system using an electric vehicle and IPFC assisted model predictive controller by Vineet Kumar, Vineet Kumar, Ark Dev

“…The proposed controller is benchmarked against conventional PID, fractional-order PIλDF, and MPC schemes optimized via Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA). …”
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Vessel Traffic Flow Prediction in Port Waterways Based on POA-CNN-BiGRU Model by Yumiao Chang, Jianwen Ma, Long Sun, Zeqiu Ma, Yue Zhou

“…Aiming at the stage characteristics of vessel traffic in port waterways in time sequence, which leads to complexity of data in the prediction process and difficulty in adjusting the model parameters, a convolutional neural network (CNN) based on the optimization of the pelican algorithm (POA) and the combination of bi-directional gated recurrent units (BiGRUs) is proposed as a prediction model, and the POA algorithm is used to search for optimized hyper-parameters, and then the iterative optimization of the optimal parameter combinations is input into the best combination of iteratively found parameters, which is input into the CNN-BiGRU model structure for training and prediction. …”
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Artificial intelligence for smart irrigation: Reducing water consumption and improving agricultural output by Arlanova A. A., Hojamkuliyeva B. A., Babanazarov N. Sh., Arlanov M. S.

“…Existing approaches to using artificial intelligence in agricultural technologies for predicting water needs and regulating irrigation are examined. A mathematical model based on machine learning algorithms is developed to predict the optimal water volume required for irrigation of agricultural crops. …”
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Application of HHO-CNN-LSTM-based CMAQ correction model in air quality forecasting in Shanghai by ZHENG Xinnan, LIN Kaiyan, WANG Zijing, SONG Yuanbo, SHI Yang, LU Hanyue, ZHANG Yalei, SHEN Zheng*

“…Accordingly, a correction model, which combines convolutional neural network (CNN) and long-short term memory neural network (LSTM) and optimized by harris hawks optimization algorithm (HHO) was established to enhance the accuracy of CMAQ model's prediction results for six air pollutants (SO_2, NO_2, PM_10, PM_2.5, O_3 and CO). …”
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A Crash Severity Prediction Method Based on Improved Neural Network and Factor Analysis by Chen Zhang, Jie He, Yinhai Wang, Xintong Yan, Changjian Zhang, Yikai Chen, Ziyang Liu, Bojian Zhou

“…The results showed that although the algorithms produced almost the same accuracy in their predictions, a backpropagation method combined with a nonlinear inertial weight setting in PSO produced fast global and accurate local optimal searching, thereby demonstrating a better understanding of the entire model explanation, which could best fit the model, and at last, the factor analysis showed that non-road-related factors, particularly vehicle-related factors, are more important than road-related variables. …”
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Improved Deviation Sparse Fuzzy C-Means-2D Cumulative Sum Average Filter and Modified Sine Cosine Crow Search Algorithm-Wavelet Extreme Learning Machine for Brain Tumor Detection a... by Suvashisa Dash, Satyasis Mishra, Mohammed Siddique, Demissie J. Gelmecha, Ram Sewak Singh

“…The MSCA-CSA algorithm optimizes the weights of the WELM model to increase the classification capability. …”
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Enhancing PM_2.5 Air Pollution Prediction Performance by Optimizing the Echo State Network (ESN) Deep Learning Model Using New Metaheuristic Algorithms by Iman Zandi, Ali Jafari, Aynaz Lotfata

“…This study evaluates efficient metaheuristic algorithms for optimizing deep learning model hyperparameters to improve the accuracy of PM_2.5 concentration predictions. …”
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Improving meningitis surveillance and diagnosis with machine learning: Insights from São Paulo. by Audêncio Victor, Diego Augusto Medeiros Santos, Eduardo Koerich Nery, Danilo Pereira Mori, Pamella Cristina de Carvalho Lucas, Denise Cammarota, Guillermo Leonardo Florez Montero, Fabiano Novaes Barcellos Filho, Ana Lúcia Frugis Yu, Telma Regina Marques Pinto Carvalhanas

“…These techniques can be integrated into public health protocols to improve meningitis outbreak responses and optimize patient treatment.…”
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Research on SeaTreasure Target Detection Technology Based on Improved YOLOv7-Tiny by Xiang Shi, Yunli Zhao, Jinrong Guo, Yan Liu, Yongqi Zhang

“…Experimental results demonstrate that our optimized algorithm achieves a mAP0.5 of 79.5%, representing a 2.0 percentage point improvement over the baseline YOLOv7-tiny model (77.5%) while maintaining computational efficiency at 45.2 GFLOPs. …”
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Efficient tuna detection and counting with improved YOLOv8 and ByteTrack in pelagic fisheries by Yuanchen Cheng, Zichen Zhang, Yuqing Liu, Jie Li, Zhou Fu

“…This paper proposes an automatic tuna counting method based on the YOLOv8n-DMTNet target detection algorithm combined with the improved ByteTrack tracking algorithm. …”
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Distributed denial of service (DDoS) classification based on random forest model with backward elimination algorithm and grid search algorithm by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…The present study proposes a novel dynamic prediction model for high-altitude PV efficiency, namely the GVSAO-CNN, which combines the Gravity Search Optimization Algorithm (GVSAO). …”
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A Surrogate-Assisted Gray Prediction Evolution Algorithm for High-Dimensional Expensive Optimization Problems by Xiaoliang Huang, Hongbing Liu, Quan Zhou, Qinghua Su

“…The proposed algorithm improves optimization efficiency by combining the macro-predictive ability of the even gray model in GPE for population update trends and the predictive ability of surrogate models to synergistically guide population searches in promising directions. …”
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Optimal Coordination of Directional Overcurrent Relays Using an Innovative Fractional-Order Derivative War Algorithm by Bakht Muhammad Khan, Abdul Wadood, Herie Park, Shahbaz Khan, Husan Ali

“…This innovative approach integrates the principles of fractional calculus (FC) into the conventional war optimization (WO) algorithm, significantly improving its optimization properties. …”
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