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. …”
Get full text

Reconstruction of Highway Vehicle Paths Using a Two-Stage Model by Weifeng Yin, Junyong Zhai, Yongbo Yu

“…In the first stage, a Gaussian Mixture Model (GMM) is integrated into a path choice model to estimate the mean and standard deviation of travel times for each road segment, utilizing an improved Expectation Maximization (EM) algorithm. In the second stage, based on the estimated time parameters, path choice prior probabilities and observed data are combined using maximum likelihood estimation to infer the most probable paths among candidate routes. …”
Get full text

A state-of-the-art novel approach to predict potato crop coefficient (Kc) by integrating advanced machine learning tools by Saad Javed Cheema, Masoud Karbasi, Gurjit S. Randhawa, Suqi Liu, Travis J. Esau, Kuljeet Singh Grewal, Farhat Abbas, Qamar Uz Zaman, Aitazaz A. Farooque

“…A machine learning approach using XGBoost, optimized with the Chaos Game algorithm (CGO-XGBoost), was employed to predict Kc. …”
Get full text

An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance by Abhijeet Das

Get full text

Integrative Path Planning for Multi-Rotor Logistics UAVs Considering UAV Dynamics, Energy Efficiency, and Obstacle Avoidance by Kunpeng Wu, Juncong Lan, Shaofeng Lu, Chaoxian Wu, Bingjian Liu, Zenghao Lu

“…Since UAVs’ energy storage capacity is generally low, it is essential to reduce energy costs to improve their system’s energy efficiency. …”
Get full text

可穿戴设备在卒中风险预测及卒中后管理中的应用进展 Research Progress on the Application of Wearable Devices in Stroke Risk Prediction and Post-Stroke Management... by 吴雅婷1，魏宸铭1，桑振华1，陈乐1，梁怡凡1，武剑1，2，3 (WU Yating1, WEI Chenming1, SANG Zhenhua1, CHEN Le1, LIANG Yifan1, WU Jian1,2,3)

“…Wearable devices, with their real-time capabilities and portability features, present new solutions for stroke risk prediction and post-stroke management. By integrating with health management platforms and artificial intelligence algorithms, wearable devices can significantly enhance the accuracy of risk assessment, optimize rehabilitation treatment plans, and thus improve the patients’ outcomes. …”
Get full text

Facilitating real-time LED-based photoacoustic imaging with DenP2P: An optimized conditional generative adversarial deep learning solution by Avijit Paul, Srivalleesha Mallidi

“…Signal quality can be improved by traditional noise removal algorithms, but deep learning models outperform non-learning methods. …”
Get full text

Accelerated Reconstruction of Scenes Using CUDA-Based Parallel Computing by Gui Zou, Jin Jiang, Qi Chen

“…Since the drone needs to use an embedded onboard computer and stereo matching algorithms require massive computing resources, this paper studies the optimization of CUDA-based stereo matching algorithms on embedded devices to improve the reconstruction effect of scenes and achieve rapid reconstruction, thereby reducing time costs, and enhancing drone efficiency.…”
Get full text

Truck Transportation Scheduling for a New Transport Mode of Battery-Swapping Trucks in Open-Pit Mines by Yufeng Xiao, Wei Zhou, Boyu Luan, Keyi Yang, Yuqing Yang

“…The primary objective is to minimize the total haulage cost and total waiting time. Both a genetic algorithm and an adaptive genetic algorithm are applied to solve the proposed multi-objective scheduling optimization model. …”
Get full text

Bayesian-optimized ensemble deep learning models for demand forecasting in the volatile situations: A case study of grocery demand during Covid-19 outbreaks by Nader AL Theeb, Hazem Smadi, Naser Al-qaydeh

“…Furthermore, using BO algorithm for hyperparameters tuning improved the forecasting accuracy. …”
Get full text

Data-driven intelligent productivity prediction model for horizontal fracture stimulation by Qian Li, Yiyong Sui, Mengying Luo, Bin Guan, Lu Liu, Yuan Zhao

“…Field validation showed that the productivity prediction model achieved an average error of 7.06%, providing a basis for horizontal fracture engineering design and achieving cost reduction and efficiency improvement in oilfield development.…”
Get full text

PARAMETRIC SYNTHESIS OF MODELS FOR MULTICRITERIAL ESTIMATION OF TECHNOLOGICAL SYSTEMS by Vladimir Beskorovainyi

“…The experimental study of the method confirms the increase in the efficiency of the procedures of parametric synthesis of models built on its basis in comparison with the method of group accounting of arguments on the basis of genetic algorithms. Practical application of the results obtained in the support systems for making multicriteria design and management decisions will improve their accuracy and, on this basis, increase the functional and cost efficiency of modern TS.…”
Get full text

Construction of an oligometastatic prediction model for nasopharyngeal carcinoma patients based on pathomics features and dynamic multi-swarm particle swarm optimization support ve... by Yunfei Li, Dongni Zhang, Yiren Wang, Yiren Wang, Yiheng Hu, Zhongjian Wen, Zhongjian Wen, Cheng Yang, Ping Zhou, Wen-Hui Cheng

“…ObjectiveThis study aimed to develop a risk prediction model for post-treatment oligometastasis in nasopharyngeal carcinoma (NPC) by integrating pathomics features and an improved Support vector machine (SVM) algorithm, offering precise early decision support.MethodsThis study retrospectively included 462 NPC patients, without or with oligometastasis defined by ESTRO/EORTC criteria. …”
Get full text

Classification of Paddy Rice Planting Area Through Feature Selection Method Using Sentinel-1/2 Time Series Images by Shiyu Zhang, Pengao Li, Yong Xie, Wen Shao, Xueru Tian

“…Therefore, this study took Liyang City as the study area, reconstructed Sentinel-2 cloud-free time series optical images, and extracted spectral features, vegetation indexes, and other features, in combination with the polarization features of the Sentinel-1 time series radar images. The optimal feature subset was selected through the feature selection method, and machine learning algorithms were optimized for paddy rice planting area classification. …”
Get full text

Energy Management of Plug-In Hybrid Electric Vehicles for Autonomous Driving in a Following Environment Based on Fuzzy Adaptive PID Control by Jixin Wang, Yujin Zhou

“…Therefore, this study is based on a fuzzy adaptive proportional integral differential controller, combined with an improved Cuckoo search algorithm, to perform group optimization on various parameters of the control system. …”
Get full text

A carbon aware ant colony system for the sustainable generalized traveling salesman problem by Marina Lin, Laura P. Schaposnik

“…Our algorithm’s unique bi-objective optimization represents a significant advancement in sustainable transportation solutions strategically balancing cost and carbon emissions to reduce energy consumption and promote environmental responsibility.…”
Get full text

Simulating Methylamine Using a Symmetry-Adapted, Qubit Excitation-Based Variational Quantum Eigensolver by Konstantin M. Makushin, Aleksey K. Fedorov

Get full text

Deep Reinforcement Learning-Based Distribution Network Planning Method Considering Renewable Energy by Liang Ma, Chenyi Si, Ke Wang, Jinshan Luo, Shigong Jiang, Yi Song

“…Traditional heuristic algorithms are limited in scalability and struggle to address the increasingly complex optimization problems of DNP. …”
Get full text

A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images by Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza, Jamel Baili, Dina Abdulaziz AlHammadi, Hee-Chan Cho, Byoungchol Chang

“…Two novel architectures, Sparse Convolutional DenseNet201 with Self-Attention (SC-DSAN) and CNN-GRU, are fused at the network level using a depth concatenation layer, avoiding the computational costs of feature-level fusion. Bayesian Optimization (BO) is employed for dynamic hyperparameter tuning, and an Entropy-controlled Marine Predators Algorithm (EMPA) selects optimal features. …”
Get full text

Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction by GUO Li-jin, WU Hao-tian

“…Next, Fuzzy Dispersion Entropy (FuzzDE) categorized the components into high-, medium-, and low-complexity subsequences. Then, an Improved Mantis Search Algorithm (IMSA) optimized three distinct models: Bidirectional Long Short-Term Memory (BiLSTM) for high-complexity components, Least Squares Support Vector Regression (LSSVR) for medium-complexity components, and Extreme Learning Machine (ELM) for low-complexity components. …”
Get full text