Kinematics Analysis and Scale Synthesis of a Novel Spherical Parallel Mechanism by Zhen Chang, Chengbo Wang, Gaofeng Wang, Jianshe Gao

“…Taking the workspace and global mean dexterity as the optimization goals，the particle swarm optimization algorithm （PSO） is used to synthesize the structure parameters of the mechanism. …”
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Cloud edge end network resource allocation for thermostatically controlled load aggregation regulation by Yi LIU, Xin WU

“…Thermostatically controlled load is a flexible load that controls temperature regulation, such as air conditioning and electric water heaters.As a crucial demand side resource, flexible aggregation and regulation of load clusters can fully mobilize clean energy consumption capacity and ensure the balance between supply and demand of the power grid.Due to the common occurrence of thermostatically controlled loads in commercial office buildings and residential areas, a relatively stable control and transmission method can be adopted.Therefore, an efficient hierarchical transmission network is introduced to achieve data transmission and information interaction between loads and the power grid, and to flexibly, real-time, and accurately utilize the adjustable potential of load clusters.Firstly, an information interaction architecture of load IoT which structured “central cloud-edge cloud-regional load controller-thermostatically controlled load”was proposed.Then, for the “end edge”part, considering the requirements of different aggregation control tasks, an improved clustering algorithm was used to classify the tasks and reduce transmission overhead.For the “end-side” part, an improved clustering algorithm was used to optimize the transmission distance.For the edge-cloud collaboration part, a subchannel resource allocation algorithm was designed based on stable matching and water injection algorithms.The binary particle swarm optimization algorithm was used to solve the task upload decision problem.Finally, the effectiveness of the proposed model and algorithm is verified through simulation, and comparative experiments are also conducted.…”
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Hybrid Technique to Improve the River Water Level Forecasting Using Artificial Neural Network-Based Marine Predators Algorithm by Sarah J. Mohammed, Salah L. Zubaidi, Nadhir Al-Ansari, Hussein Mohammed Ridha, Nabeel Saleem Saad Al-Bdairi

“…MPA-ANN algorithm’s performance is compared with recent constriction coefficient-based particle swarm optimization and chaotic gravitational search algorithm (CPSOCGSA-ANN) and slime mold algorithm (SMA-ANN) to reduce uncertainty and raise the prediction range. …”
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A Novel Energy Consumption Prediction Model Integrating Real-Time Traffic State Recognition and Velocity Prediction of BEVs by Yue Li, Yu Jiang, Jianhua Guo, Dong Xie

“…In the energy consumption prediction stage, a particle swarm optimization-radial basis function neural network (PSO-RBFNN) model is employed to estimation the energy consumption. …”
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Forecasting Chinese Wind Power Installed Capacity Using a Novel Grey Model with Parameters Combination Optimization by Xiaoshuang Luo, Bo Zeng, Hui Li, Wenhao Zhou

“…Firstly, considering the modeling mechanism and process, the order of accumulation generation of the grey prediction model is optimized by Particle Swarm Optimization (PSO) Algorithm. Secondly, as different orders of accumulation generation correspond to different parameter matrixes, the background value coefficient of the grey prediction model is optimized based on the optimal accumulation order. …”
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A Competitive Bilevel Programming Model for Green, CLSCs in Light of Government Incentives by Arsalan Rahmani, Meysam Hosseini, Amir Sahami

“…A metaheuristic quantum binary particle swarm optimization (PSO) is developed via Benders decomposition algorithm to solve the proposed model. …”
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Optimal Allocation and Sizing of Multiple DGs with Reactive Power Capabilities in a Three-Phase Unbalanced Distribution System by Zahıra Aboumarıa, Selcuk Emiroglu

“…Genetic Algorithm, Pattern Search, Particle Swarm Optimization, and Grey Wolf Optimizer algorithms have been exploited in the IEEE 37 node test feeder to find the optimal location, sizes, and power factors of the DGs. …”
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Load forecasting of microgrid based on an adaptive cuckoo search optimization improved neural network by Liping Fan, Pengju Yang

“…The mean absolute percentage error (MAPE) of the ICS-BP forecasting model was 1.13%, which was very close to an ideal prediction model, and was 52.3, 32.8, and 42.3% lower than that of conventional BP, cuckoo search improved BP, and particle swarm optimization improved BP, respectively, and the root mean square error (RMSE), mean absolute error (MAE), and mean square error (MSE) of ICS-BP were reduced by 75.6, 70.6, and 94.0%, respectively, compared to conventional BP. …”
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Planning Optimization of the Distributed Antenna System in High-Speed Railway Communication Network Based on Improved Cuckoo Search by Zhaoyu Chen, Yanheng Liu, Geng Sun, Xu Zhou, Boyu Li, Shuang Liang, Qianyu Zhou

“…Moreover, ICSDC algorithm has better performance in terms of the convergence rate and accuracy compared with the conventional cuckoo search algorithm, the particle swarm optimization, and the firefly algorithm.…”
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An Intrusion Detection System Based on Deep Learning and Metaheuristic Algorithm for IOT by Bahman Sanjabi, Mahmood Ahmadi

“…In this paper, a method is presented that uses meta-heuristic algorithms such as genetic algorithm, particle swarm optimization, artificial bee colony and gray wolf to find the optimal hyperparameters for the deep learning network and the intrusion detection system is created based on these hyperparameters. …”
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Slot Parameter Optimization for Multiband Antenna Performance Improvement Using Intelligent Systems by Erdem Demircioglu, Ahmet Fazil Yagli, Senol Gulgonul, Haydar Ankishan, Emre Oner Tartan, Murat H. Sazli, Taha Imeci

“…To achieve the best ANN performance, Particle Swarm Optimization (PSO) and Differential Evolution (DE) are applied with ANN’s conventional training algorithm in optimization of the modeling performance. …”
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Early Prediction of Cardio Vascular Disease (CVD) from Diabetic Retinopathy using improvised deep Belief Network (I-DBN) with Optimum feature selection technique by T. K. Revathi, B. Sathiyabhama, S Kaliraj, Vidhushavarshini Sureshkumar

“…We used Principal Component Analysis (PCA) and Particle Swarm Optimization (PSO) algorithm for feature extraction and selection respectively. …”
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Using Improved XGBoost Algorithm to Obtain Modified Atmospheric Refractive Index by Yanbo Mai, Zheng Sheng, Hanqing Shi, Qixiang Liao

“…Given that it is difficult to obtain the atmospheric refractive index of 100 meters (m)–3000°m over the ocean, this paper proposes an improved extreme gradient boosting (XGBoost) algorithm based on comprehensive learning particle swarm optimization (CLPSO) operator to obtain them. …”
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Preventive Control Strategy of Cascading Fault considering Safety and Economy by Hui-Qiong Deng, Jie Luo, Chen-Chen Li, Pei-Qiang Li, Rong-Jin Zheng

“…The model is a two-layer optimization mathematical model, with the inner model being solved by particle swarm optimization to minimize the power grid safety margin. …”
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Sparse Signal Representations of Bearing Fault Signals for Exhibiting Bearing Fault Features by Wei Peng, Dong Wang, Changqing Shen, Dongni Liu

“…Firstly, to enhance bearing fault signals, particle swarm optimization is introduced to tune the parameters of wavelet transform and the optimal wavelet transform is used for retaining one of the resonant frequency bands. …”
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Optimal Sensor Placement for Inverse Finite Element Reconstruction of Three-Dimensional Frame Deformation by Yong Zhao, Jingli Du, Hong Bao, Qian Xu

“…Following, an optimal sensor placement was obtained through the optimal placement model solution, with the particle swarm optimization (PSO) method. Finally, the effectiveness of optimal placement was verified though the accuracy comparison of iFEM deformation reconstruction of a wing-like frame subjected to various loads for different schemes of sensor placement.…”
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Multi-objective Optimization of Combined Gray-green Infrastructure Rainwater System for Yuhuazhai Depot of Xi’an Metro by LYU Jiajie

“…Combined with the particle swarm optimization algorithm, the Matlab software is used to optimize the configuration of the green infrastructure within the depot in order to achieve effective control over the total runoff volume, peak flood, TSS (total suspended solids) and costs. …”
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Wind energy system fault classification using deep CNN and improved PSO‐tuned extreme gradient boosting by Chun‐Yao Lee, Edu Daryl C. Maceren

“…The methodology involves resampling the imbalanced SCADA dataset using synthetic minority oversampling technique (SMOTE) and near‐miss undersampling techniques, extracting deep learning features using deep convolutional neural network, and feeding them into an XGBoost (extreme gradient boosting) classifier with tuned parameters using adaptive elite‐particle swarm optimization (AEPSO). The effectiveness of the proposed method is demonstrated through validation conducted on a different imbalanced dataset showing superior performance metrics in terms of accuracy. …”
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An Artificial Intelligence-Based Hybrid Approach to Detect the Type of Buried Objects with Broad Frequency Band Antenna Systems by Ebru Efeoğlu

“…Genetic algorithm (GA), Particle Swarm Optimization (PSO), Harmony search (HA), and Evolutionary search (EA), which are among the metaheuristic optimization algorithms, were preferred as search methods in attribute selection with CFS. …”
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Applying Hybrid PSO to Optimize Directional Overcurrent Relay Coordination in Variable Network Topologies by Ming-Ta Yang, An Liu

“…The aim of this study was to apply the Nelder-Mead (NM) simplex search method and particle swarm optimization (PSO) to solve this optimization problem. …”
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