Double-layer energy transaction strategy of multi-microgrids and distribution network with leased shared energy storage by WANG Hui, WU Zuohui, LI Xin, ZOU Zhichao, ZHOU Kerui

“…In profit allocation of microgrid alliance, an asymmetric Nash bargaining method is proposed that fairly distribute profits according to the contribution size of each member in providing energy. Finally, an improved particle swarm optimization algorithm combined with the alternating direction multiplier method is adopted to solve the hybrid game model. …”
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Multi-phase simultaneous segmentation of tumor in lung 4D-CT data with context information. by Zhengwen Shen, Zhengwen Shen, Huafeng Wang, Weiwen Xi, Xiaogang Deng, Jin Chen, Yu Zhang

“…In this paper, we propose a new method based on an improved graph cut algorithm with context information constraint to find a convenient and robust approach of lung 4D-CT tumor segmentation. …”
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Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement by Jie Fang, Wenwu Li, Dunchu Chen

“…It replaces the traditional energy storage model with this model and then solves the EV and SOP collaborative planning model using a second-order conical planning algorithm with the objective function of minimizing the annual integrated cost. …”
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Reoptimization Heuristic for the Capacitated Vehicle Routing Problem by Rodrigo Linfati, John Willmer Escobar

“…Next, the local search procedure is executed to improve the solution. A classic optimization is performed on all instances using the original and new customers’ information for later comparison to minimize distance. …”
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Reliability-Based Opportunistic Maintenance Modeling for Multi-Component Systems with Economic Dependence under Base Warranty by Rongcai Wang, Zhonghua Cheng, Enzhi Dong, Chiming Guo, Liqing Rong

“…A simulated annealing (SA) algorithm is proposed to determine the optimal maintenance cost of the system and the optimal OM threshold under BW. …”
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Advanced day-ahead scheduling of HVAC demand response control using novel strategy of Q-learning, model predictive control, and input convex neural networks by Rahman Heidarykiany, Cristinel Ababei

“…More specifically, new input convex long short-term memory (ICLSTM) models are employed to predict dynamic states in an MPC optimal control technique integrated within a Q-Learning reinforcement learning (RL) algorithm to further improve the learned temporal behaviors of nonlinear HVAC systems. …”
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Agricultural Model for Allocation of Crops Using Pollination Intelligence Method by C. N. Ejieji, A. E. Akinsunmade

“…An improved version of the Flower Pollinated Algorithm called Pollination Intelligence Algorithm using an iterative scheme to override the switch parameter in Flower Pollinated Algorithm is also presented and used in solving the designed model. …”
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Green Energy Strategic Management for Service of Quality Composition in the Internet of Things Environment by Jianhao Gao

“…The simulation results reveal that MFO has good optimization effect in the abovementioned models, and the optimization effect of MFO is improved by 8% and 6% compared with the genetic algorithm and particle swarm optimization, so as to realize the green energy strategic management of QoS composition in the environment of IoT.…”
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Intelligent Cyber-Attack Detection in IoT Networks Using IDAOA-Based Wrapper Feature Selection by Mohammed Abdullah, Ryna Svyd

“…This study presents an innovative framework that integrates the Improved Dynamic Arithmetic Optimization Algorithm (IDAOA) with a Bagging technique to enhance the performance of intelligent cyber intrusion detection systems. …”
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Intelligent tuning method for service scheduling in electric power communication networks based on operational risk and QoS guarantee. by Yang Yu, YueLin Jiang, Zeng Dou, Li Cong, Wei Huang, Qiang Zhang, Yang Hu, YanJun Bi

“…Additionally, the path satisfaction of the proposed algorithm is improved by 7.4% compared to the traditional ant colony algorithm. …”
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Flexible Job Shop Scheduling Based on Energy Consumption of Method Research by Yajie Li, Longlong Li, Xiaoying Yang, Bingfeng Zhao

“…By establishing a multi-objective optimization model aimed at minimizing the maximum completion time and energy consumption, this paper solves the flexible job-shop scheduling problem considering energy consumption (GFJSP) based on an improved deep reinforcement learning algorithm, D3QN. …”
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SGO enhanced random forest and extreme gradient boosting framework for heart disease prediction by Anima Naik, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…Both models are further optimized through hyperparameter tuning using the Social Group Optimization (SGO) algorithm. …”
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Collaborative Planning for Distribution Network and PV-ESS in the Marketization Environment by Ping RAO, Yue XIANG, Haotian YAO, Youbo LIU, Junyong LIU

“…The double-layer improved particle swarm optimization algorithm was applied to run the model. …”
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Wireless-powered cooperative energy aware anycast routing in wireless sensor networks by Fazle Hadi, Sheeraz Ahmed, Abid Ali Minhas, Abdulaziz Al Mazyad, Najam ul Islam, Imran Ahmed, Nadeem Javaid

“…Results further reveal that our proposed algorithm has improved energy consumption in comparison to the non-cooperative energy aware anycast scheme and the cooperation-based robust cooperative routing protocol scheme. …”
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Selection of third-party logistics provider based on extended multimoora technique under double hierarchy linguistic single-valued neutrosophic set by Abbas Qadir, Marya Nawaz, Muhammad Ali Khan

“…The demand for third-party logistics (3PL) providers becomes an increasingly important issue for corporations seeking improved customer service and cost reduction. Currently, there is no way to select the appropriate method for selecting 3PL. …”
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GRU-based multi-scenario gait authentication for smartphones by Qi JIANG, Ru FENG, Ruijie ZHANG, Jinhua WANG, Ting CHEN, Fushan WEI

“…At present, most of the gait-based smartphone authentication researches focus on a single controlled scenario without considering the impact of multi-scenario changes on the authentication accuracy.The movement direction of the smartphone and the user changes in different scenarios, and the user’s gait data collected by the orientation-sensitive sensor will be biased accordingly.Therefore, it has become an urgent problem to provide a multi-scenario high-accuracy gait authentication method for smartphones.In addition, the selection of the model training algorithm determines the accuracy and efficiency of gait authentication.The current popular authentication model based on long short-term memory (LSTM) network can achieve high authentication accuracy, but it has many training parameters, large memory footprint, and the training efficiency needs to be improved.In order to solve the above problems a multi-scenario gait authentication scheme for smartphones based on Gate Recurrent Unit (GRU) was proposed.The gait signals were preliminarily denoised by wavelet transform, and the looped gait signals were segmented by an adaptive gait cycle segmentation algorithm.In order to meet the authentication requirements of multi-scenario, the coordinate system transformation method was used to perform direction-independent processing on the gait signals, so as to eliminate the influence of the orientation of the smartphone and the movement of the user on the authentication result.Besides, in order to achieve high-accuracy authentication and efficient model training, GRUs with different architectures and various optimization methods were used to train the gait model.The proposed scheme was experimentally analyzed on publicly available datasets PSR and ZJU-GaitAcc.Compared with the related schemes, the proposed scheme improves the authentication accuracy.Compared with the LSTM-based gait authentication model, the training efficiency of the proposed model is improved by about 20%.…”
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A Location Selection Policy of Live Virtual Machine Migration for Power Saving and Load Balancing by Jia Zhao, Yan Ding, Gaochao Xu, Liang Hu, Yushuang Dong, Xiaodong Fu

“…We propose a novel approach MOGA-LS, which is a heuristic and self-adaptive multiobjective optimization algorithm based on the improved genetic algorithm (GA). …”
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Design and Implementation of Hybrid GA-PSO-Based Harmonic Mitigation Technique for Modified Packed U-Cell Inverters by Hasan Iqbal, Arif Sarwat

“…This paper proposes a hybrid version of the GA-PSO algorithm that exploits the exploratory strengths of GA and the convergence efficiencies of PSO in determining the optimized switching angles for SHM techniques applied to modified five-level and seven-level PUC inverters. …”
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Interfered feature elimination coupled with feature group selection for wound infection detection by electronic nose. by Jia Liu, Jinglei Zhang, Shaoqi Zhang, Kaiwei Li, Xiang Li, Shuo Zhang, Hang Gu, Zhen Chen, Chao Liu, Nan Zhang, Tong Sun

“…As the precise odor-sensing equipment, the electronic nose integrates multiple advanced and sensitive sensors that can identify wound infections non-invasively and rapidly by analyzing wound characteristic odor. To reduce the cost of sensors and improve or maintain e-nose's performance, efficient optimization of sensor arrays is required. …”
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Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA by P. Sreeraj, T. Kannan, Subhashis Maji

“…In this study, artificial neural network (ANN) and genetic algorithm (GA) techniques were integrated and labeled as integrated ANN-GA to estimate optimal process parameters in GMAW to get optimum dilution.…”
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