Improving the streamflow prediction accuracy in sparse data regions: a fresh perspective on integrated hydrological-hydrodynamic and hybrid machine learning models by Saeed Khorram, Nima Jehbez

“…For each analysed series and residuals, the proposed model needs separate TCN-SARIMA models. This requires the ADPSO algorithm for parameter calibration, which elongates the computation time. …”
Get full text

Model for selective vehicle problem considering mixed fleet with capacitated electric vehicles by Jiacheng Li, Masato Noto, Yang Zhang, Jia Guo

“…Subsequently, an adaptive large neighborhood search algorithm, improved on the basis of simulated annealing principles and local search algorithms, is proposed. …”
Get full text

Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

“…Given the complexity of the model, a leader–follower methodology based on the vortex search algorithm (VSA) is employed to determine the conductor caliber and load phase configuration, in conjunction with the three-phase successive approximations power flow method to compute the objective function. …”
Get full text

Optimization Study of Centrifugal Fan Volute Parameters based on Non-dominated Sorting Genetic Algorithm III Algorithm by J. L. Li, X. J. Wang, H. Gong, J. J. Wang

“…An efficient and accurate BP neural network was established as a surrogate model for predicting volute performance, and optimal design parameter combinations were obtained using the NSGA-III algorithm. …”
Get full text

Achieving comprehensive water productivity improvement: A multi-objective simulation-optimization model for water productivity-oriented irrigation water management by Gang Li, Chenglong Zhang, Zailin Huo, Yanqi Liu

“…Moreover, the proposed model emphasizes the influence of dynamic water-salt movement processes on crop growth and WP. …”
Get full text

External validation of and improvement upon a model for the prediction of placenta accreta spectrum severity using prospectively collected multicenter ultrasound data by Magdalena Kolak, Stephen Gerry, Hubert Huras, Ammar Al Naimi, Karin A. Fox, Thorsten Braun, Vedran Stefanovic, Heleen vanBeekhuizen, Olivier Morel, Alexander Paping, Charline Bertholdt, Pavel Calda, Zdenek Lastuvka, Andrzej Jaworowski, Egle Savukyne, Sally Collins, IS‐PAS group

“…Abstract Introduction This study aimed to validate the Sargent risk stratification algorithm for the prediction of placenta accreta spectrum (PAS) severity using data collected from multiple centers and using the multicenter data to improve the model. …”
Get full text

Estimating the transpiration of kiwifruit using an optimized canopy resistance model based on the synthesis of sunlit and shaded leaves by Zongyang Li, Lu Zhao, Zhengxin Zhao, Huanjie Cai, Liwen Xing, Ningbo Cui

“…This study established a rc estimation model based on a synthesis of sunlit and shaded leaves (SSL) and optimized it using Ant Colony Optimization (ACO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). …”
Get full text

ALGEBRAIC MODELS OF STRIP LINES IN A MULTILAYER DIELECTRIC MEDIUM by A. N. Kovalenko, A. N. Zhukov

“…The use of the Chebyshev basis and the improvement of the series convergence made it possible to develop an effective algorithm for calculating the basic electrodynamic parameters of the strip lines - the propagation constants and the wave impedances of the natural waves. …”
Get full text

A Novel Approach to Faster Convergence and Improved Accuracy in Deep Learning-Based Electrical Energy Consumption Forecast Models for Large Consumer Groups by A. Jayanth Balaji, Binoy B. Nair, D. S. Harish Ram, Kuruvachan Kalluvelil George

“…A clustering approach is employed to group users with similar consumption patterns resulting in 107 models. Effectiveness of models is validated with eight deep learning algorithms trained for two forecasting horizons. …”
Get full text

An effectiveness of machine learning models for estimate the financial cost of assistive services to disability care in the Kingdom of Saudi Arabia by Obaid Algahtani, Mohammed M. A. Almazah, Farouq Alshormani

“…Eventually, the modified pelican optimization algorithm (MPOA) is utilized to fine-tune the optimal hyperparameter of ensemble model parameters to achieve high predictive performance. …”
Get full text

A lightweight segmentation model toward timely processing for identification of pine wood nematode affected trees with UAV by Qiangjia Wu, Meixiang Chen, Hao Shi, Tongchuan Yi, Gang Xu, Weijia Wang, Ruirui Zhang

“…Compared to the baseline model UNet, the IoU of the affected trees class is improved by 5.6%, and the segmentation speed is accelerated by about 90%. …”
Get full text

The Application of Machine Learning Algorithms to Predict HIV Testing Using Evidence from the 2002–2017 South African Adult Population-Based Surveys: An HIV Testing Predictive Mode... by Musa Jaiteh, Edith Phalane, Yegnanew A. Shiferaw, Haruna Jallow, Refilwe Nancy Phaswana-Mafuya

“…However, there are insufficient predictive models to inform targeted HIV testing interventions in South Africa. …”
Get full text

The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market by Tang Xinfa, Wang Jingjing, Wang Yonghua, Wan Youwei

“…Compared with traditional power supply models, it reduces average electricity costs by 15% and increases renewable energy utilization efficiency by 20%.…”
Get full text

Attention community discovery model applied to complex network information analysis by Chen Ruiwu, Liang Zeran

“…This research utilizes the attention mechanism (AM) to adaptively learn the association weights among nodes and constructs a community discovery model (CDM) based on the AM. The model incorporates convolutional neural networks and spectral clustering algorithms to improve the practical application of CDMs. …”
Get full text

Leveraging assistive technology for visually impaired people through optimal deep transfer learning based object detection model by Mahir Mohammed Sharif Adam, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Samah Al Zanin

“…Finally, the parameter tuning of the fusion models is performed by using the Hiking Optimisation Algorithm (HOA) method. …”
Get full text

Research on Monthly Runoff Forecast in Dry Seasons Based on GEO-RVM Model by ZHANG Yajie, CUI Dongwen

“…To improve the accuracy of monthly runoff forecasts during dry seasons,this study proposes a forecasting method that combines the golden eagle optimization (GEO) algorithm and the relevance vector machine (RVM).On the basis of the runoff data of 67 a from a hydrological station in Yunnan Province,the monthly runoff with good correlation before the forecast month is selected as the influencing factor of forecasts,and the influencing factor is reduced in dimension by principal component analysis (PCA).The kernel width factor and hyperparameters of RVM are optimized by the GEO algorithm,and the GEO-RVM model is built to forecast the monthly runoff of the station during the dry season from November to April of the following year.Moreover,the forecast results are compared with those of the GEO-based support vector machine (SVM) model (GEO-SVM).The results demonstrate that the average relative errors of the GEO-RVM model for the monthly runoff forecasts from November to April of the following year are 8.59%,7.34%,5.97%,6.07%,5.99%,and 5.04%,respectively,which means the accuracy is better than that of the GEO-SVM model.The GEO algorithm can effectively optimize the kernel width factor and hyperparameters of RVM,and the GEO-RVM model has better forecast accuracy,which can be used for monthly runoff forecasting during dry seasons.…”
Get full text

Landslide Displacement Prediction Model Based on Optimal Decomposition and Deep Attention Mechanism by Shuai Ren, Kamarul Hawari Ghazali, Yuanfa Ji, Samra Urooj Khan

“…Experimental results demonstrate that the proposed model significantly improves predictive performance, reducing the Root Mean Square Error (RMSE) by 60% compared to the traditional XGBoost model and by 33% compared to the Empirical Mode Decomposition-BiLSTM (EMD-BiLSTM) model. …”
Get full text

Vessel Traffic Flow Prediction in Port Waterways Based on POA-CNN-BiGRU Model by Yumiao Chang, Jianwen Ma, Long Sun, Zeqiu Ma, Yue Zhou

“…Aiming at the stage characteristics of vessel traffic in port waterways in time sequence, which leads to complexity of data in the prediction process and difficulty in adjusting the model parameters, a convolutional neural network (CNN) based on the optimization of the pelican algorithm (POA) and the combination of bi-directional gated recurrent units (BiGRUs) is proposed as a prediction model, and the POA algorithm is used to search for optimized hyper-parameters, and then the iterative optimization of the optimal parameter combinations is input into the best combination of iteratively found parameters, which is input into the CNN-BiGRU model structure for training and prediction. …”
Get full text

Servitization of Job Shop Scheduling Algorithms by LIU Sheng-hui, ZHANG Xing, ZHANG Shu-li, MA Chao

“…Firstly, an OWLS based ontology data model and publication specification of scheduling algorithm resource was given, and then a quantitative matching and recommending method based on weighted multidimensional feature fusion was presented, in order to improve the satisfaction of algorithm service requesters and the economic benefits of algorithm resource providers. …”
Get full text

A Scalable Ensemble Learning-Based Model for Optimal Placement of Circuit Breaker and Sectionalizer in Power Distribution Systems with the Aim of Reliability Improvement by Mehrdad Ebrahimi, Mohammad Rastegar

Get full text