A graph-based sensor recommendation model in semantic sensor network by Yuanyi Chen, Yihao Lin, Peng Yu, Yanyun Tao, Zengwei Zheng

“…We use the improved fast non-dominated sorting algorithm to obtain the local optimal solutions of sensor data set, and we apply the simple additive weight algorithm to characterize and sort local optional solutions. …”
Get full text

Inter-Object Navigation of Unmanned Aerial Vehicles to Increase the Efficiency and Accuracy of Inspection of Power Lines by Tymochko O., Fustii V., Kolesnyk G., Olizarenko S., Kalashnyk G., Kulish R., Tymoschuk O., Galinskji D.

“…Solving the problem of multi-criteria optimization of the drone team flight route planning made it possible to reduce the cost of monitoring critical infrastructure facilities while improving its efficiency and accuracy. …”
Get full text

Towards precision agriculture: metaheuristic model compression for enhanced pest recognition by Sana Parez, Norah Saleh Alghamdi, Tahir Mahmood, Waseem Ullah, Muhammad Attique Khan, Taha Houda, Naqqash Dilshad

“…The core of this approach integrates InceptionV3 as a backbone feature extractor to capture rich and discriminative features, enhanced further using a channel attention (CA) mechanism for feature refinement. To reduce model complexity and improve deployment feasibility, a metaheuristic optimization algorithm was incorporated that significantly reduces computational overhead without compromising performance. …”
Get full text

Enhanced AUV Autonomy Through Fused Energy-Optimized Path Planning and Deep Reinforcement Learning for Integrated Navigation and Dynamic Obstacle Detection by Kaijie Zhang, Yuchen Ye, Kaihao Chen, Zao Li, Kangshun Li

“…This paper introduces a novel hybrid framework that synergistically fuses a Multithreaded Energy-Optimized Batch Informed Trees (MEO-BIT*) algorithm with Deep Q-Networks (DQN) to achieve robust AUV autonomy. …”
Get full text

AlgaeClass_Net: Optimizing Few-Shot Marine Microalgae Classification With Multi-Scale Feature Enhancement Network by Dan Liu, Guihong Yuan, Huachao Tan, Yanbo Jiang, Hai Bi, Yuan Cheng

Get full text

Evaluation method of e-government audit information based on big data analysis by Jingui He, Hansi Ya

“…Furthermore, a parallel PSO-RF algorithm combining Particle Swarm Optimization (PSO) and Random Forest (RF) is designed to enhance classification performance and computational efficiency. …”
Get full text

A statistical study on factors influencing piezoelectric properties of upside-down composites towards machine learning-driven development for recycling by Sivagnana Sundaram Anandakrishnan, Suhas Yadav, Mohadeseh Tabeshfar, Mikko Nelo, Jani Peräntie, Yang Bai

“…The approach lays down a foundation for scaling up the optimization of the recycled materials by providing training and/or testing datasets for possible machine learning algorithms via potential high-throughput manufacturing routes.…”
Get full text

Power Dispatch Stability Technology Based on Multi-Energy Complementary Alliances by Yiming Zhao, Chengjun Zhang, Changsheng Wan, Dong Du, Jing Huang, Weite Li

“…It aims to enhance dispatch stability and energy utilization through an innovative Distributed Overlapping Coalition Formation (DOCF) model. A distributed algorithm utilizing tabu search is proposed to solve the complex optimization problem in power resource allocation. …”
Get full text

GNSS Precipitable Water Vapor Prediction for Hong Kong Based on ICEEMDAN-SE-LSTM-ARIMA Hybrid Model by Jie Zhao, Xu Lin, Zhengdao Yuan, Nage Du, Xiaolong Cai, Cong Yang, Jun Zhao, Yashi Xu, Lunwei Zhao

“…This process significantly reduces modeling complexity and improves computational efficiency. …”
Get full text

Study on the Method of Vineyard Information Extraction Based on Spectral and Texture Features of GF-6 Satellite Imagery by Xuemei Han, Huichun Ye, Yue Zhang, Chaojia Nie, Fu Wen

“…Moreover, the RF model, which amalgamates spectral and texture features, exhibits a notable 13.59% increase in accuracy versus the spectral-only model and a 14.92% improvement over the texture-only model. …”
Get full text

A Hybrid GRA-TOPSIS-RFR Optimization Approach for Minimizing Burrs in Micro-Milling of Ti-6Al-4V Alloys by Rongkai Tan, Abhilash Puthanveettil Madathil, Qi Liu, Jian Cheng, Fengtao Lin

“…Moreover, the GRA-TOPSIS-RFR method significantly outperforms existing optimization and prediction models, with the integration of the RFR model enhancing prediction accuracy by 42.6% compared to traditional linear regression approaches. …”
Get full text

Short-Term Traffic Flow Forecasting Model Based on GA-TCN by Rongji Zhang, Feng Sun, Ziwen Song, Xiaolin Wang, Yingcui Du, Shulong Dong

“…Therefore, a short-term traffic flow forecasting model GA-TCN based on genetic algorithm (GA) optimized time convolutional neural network (TCN) is proposed in this paper. …”
Get full text

Development of a manipulator kinematic model using Abb Robot Studio by Артем Бронніков, Марія Бендеберя

“…The optimization of trajectories and collision management allowed to reduce the maintenance and operation costs of the robot, which led to an overall reduction in production costs, which will also be reflected in long-term use. …”
Get full text

Inversion of snow geophysical parameters using the VHR PAZ X-band dual polarimetric SAR data: first known experiments in the Himalayan region by Hemant Singh, Divyesh Varade

“…In the present work, we utilized the copolar phase difference (CPD) for SD and Integral Equation model (IEM) for snow density. In this study, we proposed an improved algorithm for SD inversion, instead of relying on a single in-situ snow density value, we incorporated a range of snow densities (0.15 to 0.27 g/cm3), optimizing the axial ratio between 1.13 and 1.17. …”
Get full text

Research on Control System for Material Transport Vehicle Based on Stacking Model by LIU Yuanming, TANG Lingsi, Zen Shuhua

“…Finally, the control system was reinforced using an improved proportional-integral-differential (PID) control algorithm to optimize the control performance. …”
Get full text

Parallel Bayesian Optimization of Thermophysical Properties of Low Thermal Conductivity Materials Using the Transient Plane Source Method in the Body-Fitted Coordinate by Huijuan Su, Jianye Kang, Yan Li, Mingxin Lyu, Yanhua Lai, Zhen Dong

“…A parallel Bayesian optimization algorithm based on a multi-objective hybrid strategy (MHS) is proposed based on an inverse problem. …”
Get full text

Collaborative multiview time series modeling for vehicle maintenance demand prediction by Fanghua Chen, Deguang Shang, Gang Zhou, Ke Ye, Fujie Ren, Guofang Wu

“…To enhance the interaction between distinct time points and temporal dependencies, we developed a dependency-aware learning algorithm that effectively integrates and weighs the information and dependencies at each time step, thereby improving the model’s ability to capture the complex relationships among maintenance projects over time. …”
Get full text

Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

“…Two stage-specific models were constructed, with the number of hidden layer neurons, dropout rate, and batch size determined by the optimal solutions obtained via GWO. …”
Get full text

Methodological Tools for Evaluating Effectiveness of Capital Construction Projects of Oil Producing Enterprises by E. L. Chazov, V. P. Grakhov, O. L. Simchenko

“…Due to the fact that most of the large oil fields in Russia, characterized by high production costs, are at the final stage of development; the issue of cost optimization has become increasingly important in recent years. …”
Get full text

Nonlinear Compensation of the Linear Variable Differential Transducer Using an Advanced Snake Optimization Integrated with Tangential Functional Link Artificial Neural Network by Qiuxia Fan, Xinqi Zhang, Zhuang Wen, Lei Xu, Qianqian Zhang

“…First, the Latin hypercube sampling method and the Levy flight method are introduced into the snake optimization (SO) algorithm, which enhances the global search ability and diversity preservation ability of the SO algorithm and effectively solves the common overfitting and local optimal problems in the training process of the gradient descent method. …”
Get full text