Research on dust identification and concentration detection method based on machine vision by Luyang TU, Qinghua CHEN, Yingsong CHENG, Bingyou JIANG

“…Aiming at the problem that the current machine vision algorithm fails to combine position information with concentration value in the field of dust detection, we propose an algorithm that combines improved YOLOv5 with multivariate model. …”
Get full text

Optimal Decision-making Model for Power Grid Maintenance Scheduling Considering Comprehensive Supply-Demand Factors by Hui LIU, Qianjun JIANG, Qianjin GUI, Lei WANG, Hongqiang TIAN, Jingjing WANG, Hejun YANG

“…Finally, a real power grid case is used for simulation analysis, which has verified the correctness and effectiveness of the proposed model and algorithm.…”
Get full text

Fine-tuning text-to-SQL models with reinforcement-learning training objectives by Xuan-Bang Nguyen, Xuan-Hieu Phan, Massimo Piccardi

“…For this reason, in this paper we explore the use of reinforcement learning to improve the performance of models of more conservative size, which can fit within standard user hardware. …”
Get full text

A method of identification and localization of tea buds based on lightweight improved YOLOV5 by Yuanhong Wang, Yuanhong Wang, Jinzhu Lu, Jinzhu Lu, Qi Wang, Qi Wang, Zongmei Gao

“…The improved model was denoted as YOLOV5M-SBSD and compared and analyzed with other mainstream target detection models. …”
Get full text

An Optimized Hybrid Model for Perishable Product Quality Inference in the Food Supply Chain by Muhammad Asrol, . Suharjito, Riyanto Jayadi

“…This research contributes to improving the model by employing genetic algorithms in optimizing the inference model by activating only five out of seven rules. …”
Get full text

ProBoost: Reducing Uncertainty Using a Boosting Method for Probabilistic Models by Fabio Mendonca, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias, Antonio G. Ravelo-Garcia, Mario A. T. Figueiredo

“…Just as boosting algorithms aim at obtaining accurate ensembles of simple classifiers, using a process guided by the accuracy of each of these classifiers, the method proposed in this paper builds an ensemble guided by the uncertainty of each of its individual models. …”
Get full text

Reinforcement learning-based multi-model ensemble for ocean waves forecasting by Weinan Huang, Xiangrong Wu, Xiangrong Wu, Haofeng Xia, Haofeng Xia, Haofeng Xia, Xiaowen Zhu, Yijie Gong, Xuehai Sun

“…The model ensemble algorithm effectively reduces systematic biases, improving both the stability and accuracy of wave predictions. …”
Get full text

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.…”
Get full text

The Utilization of a Naïve Bayes Model for Predicting the Energy Consumption of Buildings by Behnam Sadaghat, Ali Javadzade Khiavi, Babak Naeim, Erfan Khajavi, Hadi Sadaghat, Amir Reza Taghavi Khanghah

“…These algorithms are employed to improve HVAC system control, equipment sizing, energy management, and cost reduction. …”
Get full text

PM2.5 concentration prediction using machine learning algorithms: an approach to virtual monitoring stations by Ahmad Makhdoomi, Maryam Sarkhosh, Somayyeh Ziaei

“…The results presented that among the four ML algorithms, GBR confirmed good model performance compared to the other models, with the lowest MSE (5.33) and RMSE (2.31), as well as high accuracy measures. …”
Get full text

Modeling and Solving the Multi-Objective Vehicle Routing Problem with Soft and Fuzzy Time Windows by Ailing Chen, Tianao Li

“…Therefore, this paper considers both soft time windows and fuzzy time windows, improving upon the traditional VRPSTW and VRPFTW models to establish a more comprehensive and realistic model called the Vehicle Routing Problem with Soft Time Windows and Fuzzy Time Windows (VRPSFTW). …”
Get full text

Cutting-Edge Stochastic Approach: Efficient Monte Carlo Algorithms with Applications to Sensitivity Analysis by Ivan Dimov, Rayna Georgieva

“…This knowledge helps in identifying critical factors that significantly influence the model’s outcomes and can guide efforts to improve the accuracy and reliability of predictions. …”
Get full text

Emission prediction and optimization of methanol/diesel dual-fuel engines based on ITransformer-BiGRU and NSGA-III by Mingzhang Pan, Xinxin Cao, Changcheng Fu, Shengyou Liao, Xiaorong Zhou, Wei Guan

“…Firstly, a data cleaning method based on isolated forest and correlation analysis is designed to improve the stability of the system. Secondly, a hybrid emission prediction model based on improved Transformer (ITransformer) and Bidirectional Gated Recurrent Unit (BiGRU) is built to obtain an accurate mathematical model between control parameters and emissions. …”
Get full text

Optimization model and heuristic solution method for multi-channel cooperative sensing in cognitive radio networks by Wei YANG, Dong-song BAN, Huan-zhong LI, Wen-hua DOU

“…An optimization model under the scenario where multi-channels are cooperatively sensed and used by multi-secondary users (SU) was proposed.The model aims to maximize the system throughput and optimizes the parameters including the sensing time and the weight coefficient of the sampling result of each SU for each channel,meanwhile the false access probability for each channel must not violate the given constraints.To solve this non-linear optimization model,a sequential parameters optimization method(SPO)was proposed.The method begins with deriving the lower bound of the objective function of the optimization model.Then it maximizes this lower bound by optimizing the weight coefficients through solving a series of sub-optimal problems using Lagrange method,and finally finding an optimized sensing time parameter by the golden search algorithm.Extensive experiments by simulations demonstrate the effectiveness of the proposed method and the advantage of the proposed model on improving the system throughput.…”
Get full text

Prediction of Water Quality in Agricultural Watersheds Based on VMD-GA-LSTM Model by Yuxuan Luo, Xianglan Meng, Yutong Zhai, Dongqing Zhang, Kaiping Ma

“…In order to solve the nonlinear and non-stationary characteristics of water quality data, this paper proposes a combined model based on variational modal decomposition and genetic algorithm optimization of long short-term memory networks (VMD-GA-LSTM) for agricultural watershed water quality prediction. …”
Get full text

Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters by Tinggui Chen, Shiwen Wu, Jianjun Yang, Guodong Cong, Gongfa Li

“…Finally, through a case study, the effectiveness and efficiency of the proposed model and algorithm are verified.…”
Get full text

Dual objective multimodal transportation path optimization based on different carbon tax mechanisms under uncertain demand by Xu Zhang, Hongzhu Chen, Haiyan Zhang, Xumei Yuan

Get full text

Robust Tracking Control of Piezoelectric Actuators Using Super-Twisting Sliding Mode With Bouc-Wen Hysteresis Model-Based Enhanced Jaya Algorithm by Nguyen Thi Thu Hang, Nguyen Ngoc Son

“…The Bouc-Wen model, which captures the nonlinear hysteretic behavior of the PZT actuator, is estimated using a modified Jaya algorithm enhanced with Lévy flight distribution (called LeJaya). …”
Get full text

Development of interaction model for air traffic controllers and pilots using discrete mathematics methods by A. I. Stepnova, V. I. Kochergin, S. M. Stepanov, V. A. Borsoev

“…The purpose of the article is to create a database of errors and to develop an algorithm for a situational decision-making model taking into account availability of potential errors of air traffic controllers and pilots. …”
Get full text

An Analytical Model for Dynamic Spectrum Sensing in Cognitive Radio Networks Using Blockchain Management by Nikhil Kumar Marriwala, Sunita Panda, Chandran Kamalanathan, Narayanan Sadhasivam, Vootla Subba Ramaiah

Get full text