Rapid Detection of Key Phenotypic Parameters in Wheat Grains Using Linear Array Camera by Wenjing Zhu, Kaiwen Duan, Xiao Li, Kai Yu, Changfeng Shao

“…The errors estimating the comprehensive grain length of five wheat varieties using the extraction algorithm developed in this study, the determination coefficient and root mean square error indices, were 0.986 and 0.0887, respectively, compared with manual measurements. …”
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Intelligent and automatic irrigation system based on internet of things using fuzzy control technology by Xinying Liu, Zhihuan Zhao, Amin Rezaeipanah

“…This paper presents an automatic, low-cost intelligent irrigation system based on a fuzzy rule-based inference approach and an energy-aware routing algorithm. …”
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Integrating artificial intelligence into thermodynamics: A new paradigm for sustainable future by Marwan Al-Raeei

“…In addition, we examine the application of AI-driven optimization techniques, such as genetic algorithms and reinforcement learning, which have proven essential for improving energy efficiency and reliability across various industries. …”
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Maglev Derived Systems: An Interoperable Freight Vehicle Application Focused on Minimal Modifications to the Rail Infrastructure and Vehicles by Jesus Felez, Miguel A. Vaquero-Serrano, William Z. Liu, Carlos Casanueva, Michael Schultz-Wildelau, Gerard Coquery, Pietro Proietti

“…Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. …”
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Tracking and Disturbance Suppression of the Radio Telescope Servo System Based on the Equivalent-Input-Disturbance Approach by Lei Yang, Na Wang, Zhiyong Liu, Ning Li

“…An EID estimator is developed using the difference between the estimated output of the state observer and the measurement output and then the estimate of the EID is fed forward into the control input to reject the disturbance. A cost function with clear physical meaning is selected and the weighting parameters are adjusted for the optimal controller to improve tracking performance. …”
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Post-integration based point-line feature visual SLAM in low-texture environments by Yanli Liu, Zhengyuan Feng, Heng Zhang, Wang Dong

“…Abstract To address the issues of weak robustness and low accuracy of traditional SLAM data processing algorithms in weak texture environments such as low light and low contrast, this paper first studies and improves the data feature extraction method, optimizing the AGAST-based feature extraction algorithm to adaptively adjust the extraction threshold according to the gradient size of different data features. …”
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Performance and emission analysis of CI engine fueled with Dunaliella salina biodiesel and TiO₂ nanoparticle additives: Experimental and ANN-based Predictive Approach by V Hariram, S Balamurugan, R Mohan, R Karthick, Nandagopal Kaliappan, K Barathiraja, J Godwin John, K Kamakshi Priya

“…Experimental results identified the D80DuBD20TiO₂ blend at a compression ratio of 18 (CR18) as optimal, demonstrating improved combustion efficiency and reduced emissions. …”
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Intelligent Scheduling of a Pulsating Assembly Flow Shop Considering a Multifunctional Automated Guided Vehicle by Hailong Song, Shengluo Yang, Shuoxin Yin, Junyi Wang, Zhigang Xu

“…Our experimental results demonstrate that the proposed strategies significantly improve the production efficiency of pulsating assembly workshops, reduce AGV scheduling costs, and optimize overall production workflows. …”
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Theoretical analysis of MOFs for pharmaceutical applications by using machine learning models to predict loading capacity and cell viability by Bader Huwaimel, Saad Alqarni

“…Principal Component Analysis (PCA) was applied to reduce dimensionality, and the Water Cycle Algorithm was used to optimize hyperparameters. Evaluation metrics, including R2, Root Mean Squared Error (RMSE), and maximum error, indicated that the QR-MLP model outperformed the other models, achieving test R2 scores of 0.99917 for Drug Loading Capacity and 0.99111 for Cell Viability. …”
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Fuzzy logic-based simulation of a weighted integrated GNSS receiver for mitigating blocking interference effects by K. Bahmani, M.R. Mosavi, A. Sadr

“…To this end, a novel approach is proposed to improve the performance of receivers in integrated GNSS systems, which includes two-stage acquisition, fuzzy logic, and a weighting mechanism based on the Weighted Least Squares (WLS) algorithm. …”
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Enhancing Resilience and Efficiency in Power System: A Five-Level Dynamic Planning Model by Mahnaz Rezaei, Mohammad Tolou Askari, Meysam Amirahmadi, Vahid Ghods

“…Its purposes are to improve resilience, minimize input transmission costs, and minimize operating costs. …”
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Designing and implementing a Web-based real time routing service for crisis management (a case study for district 11 of Tehran) by javad sadidi, seyed hassan hosseini sajedi

“…According to the obtained results, the path’s length and traffic’s volume variables have the most important role in target function formation (travel cost) therefore the specific path will be selected as the optimal path, with the minimized distance between the destination and the traffic volume. …”
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Multi-objective Predictive Control of Gas Turbine System Based on T-S Fuzzy Model by Guolian HOU, Xiaoyan DAI, Linjuan GONG, Haixin XU, Jianhua ZHANG

“…Next, the multi-objective predictive controller is designed in which the load tracking index and economic index are defined and combined into a comprehensive multi-objective cost function. Then, in order to improve the settling speed of load tracking process, the simultaneous heat transfer search algorithm is employed to optimize the cost function and determine the control variables. …”
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A Two-Stage Site Selection and Capacity Determination Method for Energy Storage Power Stations Based on HC-MOPSO by Wangwang BAI, Dezhou YANG, Wanwei LI, Tao WANG, Yaozhong ZHANG

“…The MOPSO algorithm embedded in power flow calculation is designed to solve the model. …”
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Hybrid modeling of adsorption process using mass transfer and machine learning techniques for concentration prediction by Jing Lv, Lei Wang

“…Prior to model training, the dataset underwent rigorous preprocessing including outlier removal using the z-score method and normalization. To improve model performance, hyperparameters were optimized using the bio-inspired Barnacles Mating Optimizer (BMO) algorithm. …”
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Design of Wireless Communication Test System for Rail Transit Based on Virtual Drive Test by ZHANG Chao

“…Simulation results show that the system can simulate and play back the real outfield network environments, effectively improve the hardware performance of wireless terminal and optimize the software algorithm of terminal control.…”
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Enhancing high pressure pulsation test bench performance: a machine learning approach to failure condition tracking by Aslı Aksoy, Ömer Haki

“…The utilization of FCTT has enabled the prediction of HPPT failures, the optimization of maintenance schedules, the minimization of downtime, and the improvement of maintenance practices. …”
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Elastic net with Bayesian Density Estimation model for feature selection for photovoltaic energy prediction by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…Research investigations demonstrate that the ELNET-BDE model attains significantly lower Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) than contesting Machine Learning (ML) algorithms like Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting Machines (GBM). …”
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Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping by Oluwatobi Emmanuel Dare, Kennedy Okokpujie, Emmanuel Adetiba, Olabode Idowu-Bismark, Abdultaofeek Abayomi, Raymond Jules Kala, Emmanuel Owolabi, Udeme Christopher Ukpong

“…The model performance was evaluated using mean square error (MSE) and mean absolute error (MAE). 12 different experiments were carried out varying the training parameters of the CGAN architecture to obtain an optimal model. The achieved root mean square error (RMSE) is 0.1145dBm and MAE is 0.0820dBm, which shows the deviation between the ground truth and the generated REM. …”
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Coal mining equipment lifecycle management system architecture and key technology by Yihui PANG, Jinglong BI, Pengzhe YUAN, Baofu ZHAO, Ziwei DING

“…An optimization algorithm and software platform for comprehensive mining equipment selection were developed, and a method for constructing a series spectrum and coding system for coal mining equipment was proposed. …”
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