A Travel Demand Response Model in MaaS Based on Spatiotemporal Preference Clustering by Songyuan Xu, Yuqi Liang, Jing Zuo

“…To respond to travel demand in the MaaS system, improve transport efficiency, and optimize the framework of MaaS, we propose a travel demand response model based on a spatiotemporal preference clustering algorithm that considers the impact of travel preferences and features of the MaaS system to improve travel demand response and achieve full coverage of travel demands. …”
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Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

“…Bayesian optimization fine-tuned each model's hyperparameters to identify the optimal model-FS combination. …”
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Hyperspectral Anomaly Detection by Spatial–Spectral Fusion Based on Extreme Value-Entropy Band Selection and Cauchy Graph Distance Optimization by Song Zhao, Yali Lv, Wen Zhang, Lijun Wang, Zhiru Yang, Gaofeng Ren, Bin Wang, Xiaobin Zhao, Tongwei Lu, Jiayao Wang, Wei Li

“…Second, to enhance the model’s adaptability to non-Gaussian backgrounds and maximize spectral information utilization, we propose a Cauchy graph distance-optimized RX anomaly detection approach. …”
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A bearing fault diagnosis method based on hybrid artificial intelligence models. by Lijie Sun, Xin Tao, Yanping Lu

“…The process employs Maximum Second-order Cyclostationary Blind Deconvolution (CYCBD) to filter out noise from the vibration signals emitted by bearings; secondly, considering the issue with the conventional Harris Hawks Optimization (HHO) algorithm which tends to prematurely converge to local optima, the differential evolution mutation operator is introduced and the escape energy factor is improved from linear to nonlinear in IHHO; then, a double-layer network model based on DBN-ELM is proposed, to avoid the number of hidden layer nodes of DBN from human experience interference, and IHHO is used to optimize DBN structure, which is denoted as IHHO-DBN-ELM method; with the optimal structure is obtained by using a combined IHHO optimized DBN and ELM; in conclusion, the proposed IHHO-DBN-ELM approach is applied to the bearing fault detection using the Western Reserve University's bearing fault dataset. …”
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Menstrual cycle inspired latent diffusion model for image augmentation in energy production by Gamal M. Mahmoud, Mostafa Elbaz, Wael Said, Amira A. Elsonbaty

“…First, a menstrual cycle-inspired metaheuristic algorithm is integrated to improve generated images’ pixel integrity and structural coherence. …”
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Evaluating Medical Entity Recognition in Health Care: Entity Model Quantitative Study by Shengyu Liu, Anran Wang, Xiaolei Xiu, Ming Zhong, Sizhu Wu

“…These gaps hinder the development of optimized NER models for medical applications. …”
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Internal Control Model of Enterprise Financial Management Based on Market Economy Environment by Qian Li

“…In order to better solve the problems existing in the internal environment, risk assessment, and internal supervision of enterprise financial management, this paper proposes a method of enterprise financial analysis and control model based on artificial neural network algorithm. …”
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A Multi-Objective Decision-Making Method for Optimal Scheduling Operating Points in Integrated Main-Distribution Networks with Static Security Region Constraints by Kang Xu, Zhaopeng Liu, Shuaihu Li

“…Subsequently, a scheduling optimization model is formulated to minimize both the system generation costs and the comprehensive risk, where the adaptive grid density-improved multi-objective particle swarm optimization (AG-MOPSO) algorithm is employed to efficiently generate Pareto-optimal operating point solutions. …”
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Increasing Minority Recall Support Vector Machine Model for Imbalanced Data Classification by Chunye Wu, Nan Wang, Yu Wang

“…In the experiments, the effects of different parameters on the performance of the algorithm were analyzed, and the optimal parameters for a recall rate of 1 were determined. …”
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A Hybrid Deep Learning Model for UAV Path Planning in Dynamic Environments by Junchi Zhang, Yanning Xian, Xun Zhu, Hongtao Deng

“…However, the commonly used Rapidly-exploring Random Tree (RRT) algorithm for UAV path planning often generates suboptimal paths that require extensive post-processing to improve. …”
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Medium- and Long-Term Optimal Stochastic Scheduling for Inter-Basin Hydro-Wind-Photovoltaic Complementary Systems Considering Wind and Solar Output Uncertainty by Chengrui Du, Yuan Gao, Lili Wang, Xiang Li, Yichen Cui, Jian Gao

“…The model is subsequently solved using the Gurobi 11.0.3 optimization solver within the MATLAB environment. …”
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Coupled Coil Design and Magnetic Field Characteristics Analysis of Wireless Power Transfer System Based on Semi-closed Domain Coupling Resonance by ZHOU Xiwei, YANG Zewang, BAI Yehong, SHANG Xinjuan

“…In this paper, under the semi-closed nonlinear coupling state with radial, angular and radial-angle offsets, a 3D model of coupling coil is established for wireless power transmission system, and a new genetic algorithm is used to determine the parameters of the coupling coil. …”
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Efficient black-box attack with surrogate models and multiple universal adversarial perturbations by Tao Ma, Hong Zhao, Ling Tang, Mingsheng Xue, Jing Liu

“…By combining MUAPs with surrogate models, SMPack effectively overcomes the black-box constraints and improves the efficiency of generating adversarial examples. …”
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Research on the On-Line Identification of Ship Maneuvering Motion Model Parameters and Adaptive Control by Jinlai Liu, Lubin Chang, Luping Xu, Fang He, Yixiong He

“…A response-type ship maneuvering model is used, with a forgetting factor incorporated into the recursive least squares (RLS) algorithm based on the iterative least squares (ILS) method. …”
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Research on PRBP Neural Network Flood Forecasting Model in Chongyang River Basin by SI Qi, JIN Baoming, LU Wangming, CHEN Zhaoqing

“…The Poak-Ribiére conjugate gradient back propagation algorithm (PRBP) of numerical optimization technology was used, and 21 rainstorm and flood processes from 1997 to 2022 in the upper reaches of Chongyang River basin were studied. …”
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Research on PRBP Neural Network Flood Forecasting Model in Chongyang River Basin by SI Qi, JIN Baoming, LU Wangming, CHEN Zhaoqing

“…The Poak-Ribiére conjugate gradient back propagation algorithm (PRBP) of numerical optimization technology was used, and 21 rainstorm and flood processes from 1997 to 2022 in the upper reaches of Chongyang River basin were studied. …”
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A Parameter Estimation Method of DC-link Capacitor Based on Pre-charge Process of Traction Converter by LYU Gexing, ZHU Qi

“…In order to improve the reliability of the estimation, different from the traditional parameter identification algorithm based on gradient descent, the genetic algorithm is used to search for the optimal value in the range of health parameter and estimate the real parameter. …”
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A Review of Generative Design Using Machine Learning for Additive Manufacturing by Parankush Koul

“…The scalability and predictability of artificial intelligence (AI) models make handling huge data easy and enable scale-up of production without compromising quality. …”
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Modeling the Dynamic Evolution of the Vehicular Ad Hoc Networks under the City Scenario by Lili Zhang, Yueheng Li, Guoping Tan, Rongbo Zhu, Hao Chen

“…In the end, we analyze and verify the efficiency of our model by theoretical deductions and simulations, and our model will be helpful to find more efficient routing algorithm and build the more trustable simulator of VANET.…”
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A prior information-based multi-population multi-objective optimization for estimating 18F-FDG PET/CT pharmacokinetics of hepatocellular carcinoma by Yiwei Xiong, Siming Li, Jianfeng He, Shaobo Wang

“…Abstract Background 18F fluoro-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) pharmacokinetics is an approach for efficiently quantifying perfusion and metabolic processes in the liver, but the conventional single-individual optimization algorithms and single-population optimization algorithms have difficulty obtaining reasonable physiological characteristics from estimated parameters. …”
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