A Unique Bifuzzy Manufacturing Service Composition Model Using an Extended Teaching-Learning-Based Optimization Algorithm by Yushu Yang, Jie Lin, Zijuan Hu

“…Next, we address the multi-objective optimization issue through the application of extended teaching-learning-based optimization (ETLBO) algorithm. …”
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Optimizing Personalized Recommender Systems for Teachers’ Digital Learning Models Using Deep Learning Algorithms by Jun Zhong, Wenjuan Zhang

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Integrated Modeling and Optimal Operation Strategy of Building Cooling System Combining the Standardized Thermal Resistance and Genetic Algorithm by Liang Tian, Bohong Lai, Tianzhen Yang, Xingce Wang, Junhong Hao, Kaicheng Liu

“…ABSTRACT Integrated modeling and operation optimization of building energy systems is significant for improving the energy utilization efficiency and reducing carbon emission. …”
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An Optimization Model for Shell Plate Seam Landing Using Minimum Manufacturing Cost and a Solution by Genetic Algorithm by Ho Rim Pae, Min Hyok Jon, Chol Jun Pak

“…In this paper, a new optimization model and its solution method for the landing of seams and butts (for convenience, seam and butt are simply called seam) on the ship hull surface are proposed in order to improve the shipbuilding efficiency. …”
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Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms by Sawsan Akram Hassan, Mahir M. Hason, Ammar N. Hanoon, Ali A. Abdulhameed

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Modeling and Solving the Knapsack Problem with a Multi-Objective Equilibrium Optimizer Algorithm Based on Weighted Congestion Distance by Ziqian Wang, Xin Huang, Yan Zhang, Danju Lv, Wei Li, Zhicheng Zhu, Jian’e Dong

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Optimization design of urban rainwater and flood drainage system based on SWMM by Cao Xihan

“…Traditional drainage system design methods are no longer able to meet the complex needs of modern cities. To improve the overall performance of urban rainwater and flood drainage system, a coupling model of multiobjective optimization algorithm and rainstorm management model is constructed. …”
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A Novel Prediction Model for the Sales Cycle of Second-Hand Houses Based on the Hybrid Kernel Extreme Learning Machine Optimized Using the Improved Crested Porcupine Optimizer by Bo Yu, Deng Yan, Han Wu, Junwu Wang, Siyu Chen

“…For this reason, this paper develops a prediction model of the second-hand housing sales cycle based on the hybrid kernel extreme learning machine (HKELM) optimized using the Improved Crested Porcupine Optimizer (CPO), which has achieved rapid and accurate prediction. …”
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Determining Appropriate Strategy for Managing the Energy Production System in the Presence of Renewable Energy Sources and Improved Intelligence Method by Amir Sohel, Md Faisal Bin Ashab

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Two-Layer Optimal Scheduling and Economic Analysis of Composite Energy Storage with Thermal Power Deep Regulation Considering Uncertainty of Source and Load by Chao Xing, Jiajie Xiao, Xinze Xi, Jingtao Li, Peiqiang Li, Shipeng Zhang

“…The upper layer takes pumped storage as the optimization goal to improve net load fluctuation and the optimal peak load benefit; the lower layer takes the system’s total peak load cost as the optimization goal and obtains a day-before scheduling plan for the energy storage system, using an improved gray wolf algorithm to process it. …”
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An innovative coverage optimization method for smart information monitoring in agricultural IoT using the multi-strategy Pelican optimization algorithm by Wei Chen, Qike Cao, Bingyu Cao, Bo Jin

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LPBSA: Pre-clinical data analysis using advanced machine learning models for disease prediction by Dana R. Hamad, Tarik A. Rashid

“…The current study introduces an optimization algorithm, Learner Performance-Based Behavior with Simulated Annealing (LPBSA), integrated with Multilayer Perceptron (MLP) as a neural network technique to improve disease prediction accuracy. …”
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Short-Term Power Load Prediction Based on Level Processing Method and Improved GWO Algorithm by Yuntong Li

“…To address this issue, this study introduces level processing method and improved grey wolf genetic algorithm to predict short-term power load and optimize the power load prediction accuracy. …”
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SC-PA: A spot-checking model based on Stackelberg game theory for improving peer assessment by Jia Xu, Panyuan Yang, Teng Xiao, Pin Lv, Minghe Yu, Ge Yu

“…Significant findings from the empirical study and a comparison with baselines include: by showing students the spot-checking probabilities, the students’ motivation in carefully grading their peers’ submissions and the fairness of peer assessment are both apparently enhanced; compared with the best baseline, the accuracy of the SC-PA model for peer assessment is improved by 44.1%; although the accuracy of peer assessment can be improved by increasing the number of review resources, the performance gain may become insignificant when the number of resources exceeds a certain limit in real teaching practices; and most students believe that their assessment ability can be effectively improved after multiple peer assessment activities. …”
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Network Security Situational Awareness Based on Improved Particle Swarm Algorithm and Bidirectional Long Short-Term Memory Modeling by Peng Zheng, Yun Cheng, Wei Zhu, Bo Liu, Shuhong Liu, Shijie Wang, Jinyin Bai

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Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO by Enlai ZHANG, Yi CHEN, Liang SU, Ruoyu ZHONGLIAN, Xianyi CHEN, Shangfeng JIANG

“…Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. …”
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Resilience-Improving Based Optimization of Post-Disaster Emergency Maintenance Strategy for Transmission Networks by Haiping LIANG, Haoyan SHI, Yan WANG, Yingpei LIU, Xinming WANG

“…An improved particle swarm optimization (PSO) algorithm is proposed for the optimization model, which uses such methods as the multi-dimensional indefinite length coding, sub-group collaborative optimization, and Monte-Carlo-simulation-based fitness evaluation to improve the standard PSO algorithm. …”
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Grey modeling method for approximate exponential sequence of optimizing initial condition by Yun YUE, Guangyue LU

“…Grey GM（1,1）prediction method is only suitable for the prediction model of the original sequence which satisfies the characteristic of the approximate exponential through the accumulated generating operation.In order to widen the application range of the traditional grey prediction model,a new method,dubbed DGM（1,1,c,β）model（direct grey model）,was proposed to improve the accuracy of grey GM（1,1）prediction by optimizing initial conditions.DGM（1,1,c,β）model was established for the original sequence conforming to the approximate exponential and the model parameters were obtained by the particle swarm optimization algorithm.Both the simulation and analysis of the example demonstrate that the proposed method is more effective and practical.…”
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The Impact of Different Parallel Strategies on the Performance of Kriging-Based Efficient Global Optimization Algorithms by Hang Fu, Qingyu Wang, Takuji Nakashima, Rahul Bale, Makoto Tsubokura

“…A parallel efficient global optimization (EGO) algorithm with a pseudo expected improvement (PEI) multi-point sampling criterion, proposed in recent years, is developed to adapt the capabilities of modern parallel computing power. …”
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Research on Vehicle Route Optimization for Half-Open Multi-Energy Urban Distribution Considering Order Priority by Mingxuan Zhang

“…Aiming at the current problems of increasingly serious tailpipe pollution of urban distribution vehicles and irrational distribution route planning, we construct a fuel-electric hybrid multi-trip multi-center half-open joint distribution vehicle routing optimization model (F-EHOMTMDVRPOPTW) considering order priority and fuzzy time window, and introduce Tent chaotic mapping combined with an improved discrete sparrow search algorithm (DSSA) with stochastic key encoding strategy for solving. …”
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