The Correlation of Microscopic Particle Components and Prediction of the Compressive Strength of Fly-Ash-Based Bubble Lightweight Soil by Yaqiang Shi, Hao Li, Hongzhao Li, Zhiming Yuan, Wenjun Zhang, Like Niu, Xu Zhang

“…The Bayesian-optimized Random Forest model performed optimally in terms of the mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE), and the prediction performance was best. …”
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Crushing Force Prediction Method of Controlled-Release Fertilizer Based on Particle Phenotype by Linlin Sun, Xiubo Chen, Zixu Chen, Linlong Jing, Jinxing Wang, Xinpeng Cao, Shenghui Fu, Yuanmao Jiang, Hongjian Zhang

“…Comparative tests with a random forest regression, the K-nearest neighbor, a back propagation (BP) neural network, and a long short-term memory (LSTM) neural network have demonstrated that the PSO-SVM model outperforms these methods in terms of mean absolute error, root mean square error, and correlation coefficient, underscoring its effectiveness. …”
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Hardware-Centric Exploration of the Discrete Design Space in Transformer–LSTM Models for Wind Speed Prediction on Memory-Constrained Devices by Laeeq Aslam, Runmin Zou, Ebrahim Shahzad Awan, Sayyed Shahid Hussain, Kashish Ara Shakil, Mudasir Ahmad Wani, Muhammad Asim

“…A contribution of this research is the development of a novel cost function that balances the reduction of mean squared error with the constraints of model size. …”
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Pressure-Related Discrepancies in Landsat 8 Level 2 Collection 2 Surface Reflectance Products and Their Correction by Santosh Adhikari, Larry Leigh, Dinithi Siriwardana Pathiranage

“…For the green band, the reduction in error was much less due to the significantly lesser impact of aerosol on this band. …”
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THE SOLUTION TO THE PROBLEM OF USING GROUND WATER TO COOL LIVESTOCK BUILDINGS by Thay Ngok Shon, Vo Ti Tin

“…Hot climate strongly affects the animal organism alongside with the animal weight reduction and reduction the quantity of egg-laying in poultry. …”
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Logistics business management of provider in Thailand with smart logistics by Natpatsaya Setthachotsombut, Komson Sommanawat, Gritsada Sua-iam

“…This study identifies the performance outcomes: reducing errors, cost reduction, reducing complexity, labor reduction, and operational efficiency improvement. …”
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A novel conceptual design approach for autonomous underwater helicopter based on multidisciplinary collaborative optimization by Yuan-Jie Chen, Haocai Huang

“…Furthermore, the proposed LTC-SSA-BPNN algorithm accurately evaluates sailing resistance and Tsai-Wu failure index, with maximum errors of 1.64% and 9.32% respectively. Additionally, the composite pressure shell achieves a 30.4% weight reduction and a 4.1% reduction in sailing resistance while maintaining structural stability. …”
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Enhancing Supply Chain Agility and Sustainability through Machine Learning: Optimization Techniques for Logistics and Inventory Management by Vikram Pasupuleti, Bharadwaj Thuraka, Chandra Shikhi Kodete, Saiteja Malisetty

“…The study underscores the importance of adopting advanced technologies to enhance deci-sion-making, evidenced by a 12% improvement in lead time efficiency, a silhouette coefficient of 0.75 for clustering, and an 8% reduction in replenishment errors.…”
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Laurel–Yanny percept affects the speech-to-song illusion, but musical anhedonia does not by Nicholas Kathios, Benjamin M. Kubit, Nicole Grout, Jake Everard, Emma Zachary, Arushi Sankhe, Adam Tierney, Aniruddh D. Patel, Psyche Loui

“…Repeated listening to musical phrases can also lead to changes in liking, attributed to learning-related reduction of prediction errors generated by the dopaminergic reward system. …”
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Integrating BIM with Lean Principles for Enhanced Decision-making: Optimizing Insulation Material Selection in Sustainable Construction Project by Karim El Mounla, Djaoued Beladjine, Karim Beddiar

“…The tool achieved a 6% reduction in primary energy consumption, a 40% decrease in carbon footprint per $$m^2$$ and a 6% reduction in annual CO2 emissions. …”
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A river network model using a weight-based merged LSTM for multi-source monitoring integration by Jonggyu Jung, Taeseung Park, Jaegwan Park, Dogeon Lee, YoonKyung Cha

“…The model demonstrates strong forecasting performance, with mean absolute errors ranging from 0.055 to 0.518, root mean squared errors from 0.075 to 0.784, and coefficients of determination between 0.424 and 0.721. …”
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Damage Identification in Large-Scale Structures Using Time Series Analysis and Improved Sparse Regularization by Huihui Chen, Xiaojing Yuan

“…Furthermore, regarding the numerical example, the damage identification results show that the max identification errors of the proposed method are 6% among the three cases under noise-free and noise-polluted data, while the max identification errors for MFO and the regularization method are 15% and 10%, respectively. …”
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Optimizing VGOS observations using an SNR-based scheduling approach by Matthias Schartner, Bill Petrachenko, Mike Titus, Hana Krásná, John Barrett, Dan Hoak, Dhiman Mondal, Ming Hui Xu, Benedikt Soja

“…In addition, Earth orientation parameters showed significant improvement, with a 40 % to 50 % reduction in formal errors. Graphical Abstract…”
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SERF magnetometer array using concurrent amplitude-stabilized optical modulation by Ziqian Yue, Yueyang Zhai, Yuhao Wang, Xiangjin Xu, Junjian Tang

“…Moreover, the array shows high measurement consistency within 10–100 pT, with measurement errors below 0.76 pT and non-linear errors less than 2 %. …”
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Nonnegative Matrix Factorization Based Adaptive Noise Sensing over Wireless Sensor Networks by Kwang Myung Jeon, Hong Kook Kim, Sung Joo Lee, Yun Keun Lee

“…In addition, the proposed method is applied to an automatic speech recognition (ASR) system, which is a typical speech-based application, and then the average word error rate (WER) of the ASR is compared with that employing either a Wiener filter, or a conventional NMF-based noise reduction method using only a priori noise basis matrix.…”
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Numerical study of a copper oxide-based thermochemical heat storage system by Zhen Cao, Bas Joris de Leeuw, Tianchao Xie, Abhishek K. Singh

“…The model was validated within <10 % error margin by the experimental measurements of the temperature inside the reactor and the molar fraction of O2 at the reactor outlet. …”
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Denoising of acoustic emission signals from rock failure processes through ICEEMDAN combined with multiple criteria and wavelet transform by Tao Wang, Weiwei Ye, Liyuan Liu, Zhihui Zhao, Wei Huang

“…Compared to traditional wavelet denoising methods, the proposed method exhibits higher signal-to-noise ratio (SNR) improvement, as well as varying degrees of reduction in mean squared error (MSE) and total harmonic distortion (THD). …”
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A data-driven control method for ground locomotion on sloped terrain of a hybrid aerial-ground robot by Xinhang Xu, Yizhuo Yang, Muqing Cao, Thien-Minh Nguyen, Kun Cao, Lihua Xie

“…Then, we design a sliding mode controller using these predictions and establish its input-to-state stability and error bounds. Experiments show improvements of the proposed neural network in training speed and robustness over a baseline ReLU network, and a 40% reduction in tracking error compared to a baseline PID controller.…”
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Research on the Multi-Objective Optimal Design of Adjusting Mechanisms Considering Force Transmission Performance by Qi Yang, Mingxin Shan, Yangli Tian, Boyang Guan, Jingyu Zhai, Wei Sun

“…Through case studies, significant reductions in motion precision errors and the peak stagnation force and maximum differences in stagnation force were achieved, validating the feasibility of this optimization design approach.…”
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Quantum Computing-Accelerated Kalman Filtering for Satellite Clusters: Algorithms and Comparative Analysis by Shreyan Prakash, Raj Bhattacherjee, Sainath Bitragunta, Ashutosh Bhatia, Kamlesh Tiwari

“…Our quantum computing-based approach achieves a significant improvement in prediction accuracy and a reduction in mean absolute error compared to classical Kalman filtering techniques. …”
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