Metode Taguchi Untuk Optimasi Proses Engraving CNC Router G-Weike WK1212 untuk Kayu Mahoni by Dewa Kusuma Wijaya, Nur Alfathan Banoel, Tita Talitha

“…The problem of this research lies in the operational settings of the machine which are still based on estimates or assumptions. …”
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Consensus-based optimisation with truncated noise by Massimo Fornasier, Peter Richtárik, Konstantin Riedl, Lukang Sun

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Improving Global Reservoir Parameterizations by Incorporating Flood Storage Capacity Data and Satellite Observations by Youjiang Shen, Dai Yamazaki, Yadu Pokhrel, Gang Zhao

“…We demonstrated that machine‐learning FSC and satellite observations help improve reservoir parameterizations, and found that improvements in other aspects of river modeling are essential for accurately reproducing discharge patterns.…”
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Smart IoT-driven precision agriculture: Land mapping, crop prediction, and irrigation system. by Gourab Saha, Fariha Shahrin, Farhan Hasin Khan, Mashook Mohammad Meshkat, Akm Abdul Malek Azad

“…Such analysis helps to decide whether that land is suitable for farming or not. Multiple soil-parameter measuring sensors are used to identify suitable crop and fertilizer requirements for that land using IoT and machine learning. …”
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Canopy-Level Rice Yield and Yield Component Estimation Using NIR-Based Vegetation Indices by Hyeok-Jin Bak, Eun-Ji Kim, Ji-Hyeon Lee, Sungyul Chang, Dongwon Kwon, Woo-Jin Im, Do-Hyun Kim, In-Ha Lee, Min-Ji Lee, Woon-Ha Hwang, Nam-Jin Chung, Wan-Gyu Sang

“…Machine learning regression models were then used to predict yield and yield components using the log-normal parameters and individual VIs as input. …”
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PyAMARES, an Open-Source Python Library for Fitting Magnetic Resonance Spectroscopy Data by Jia Xu, Michael Vaeggemose, Rolf F. Schulte, Baolian Yang, Chu-Yu Lee, Christoffer Laustsen, Vincent A. Magnotta

“…Monte Carlo simulations were conducted to assess robustness and accuracy across various signal-to-noise ratios and parameter perturbations. <b>Results</b>: PyAMARES utilizes spreadsheet-based prior knowledge and fitting parameter settings, enhancing flexibility and ease of use. …”
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Research Progress of Computational Fluid Dynamics in Mixed Ionic–Electronic Conducting Oxygen-Permeable Membranes by Jun Liu, Jing Zhao, Yulu Liu, Yongfan Zhu, Wanglin Zhou, Zhenbin Gu, Guangru Zhang, Zhengkun Liu

“…We also highlight the challenges in current CFD research, such as high computational costs, parameter uncertainties, and model complexities, while discussing the potential of emerging technologies, such as machine learning, to enhance CFD modeling capabilities. …”
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Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

“…Existing methodologies, including regression-based models, heuristic approaches, and optimization-driven methods, struggle to generalize across dynamic environments due to their reliance on static parameter configurations. Machine learning-based approaches have improved localization accuracy but require extensive labeled datasets and often lack adaptability to real-time variations. …”
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Research on green supply chain finance risk identification based on two-stage deep learning by Ying Liu, Sizhe Li, Chunmei Yu, Mingli Lv

“…In the first stage, we employ Generative Adversarial Network (GAN) to generate minority class default samples, and utilize Stacked Auto-Encoder (SAE) to extract data features with closed-form parameter calculation capability. In the second stage, the obtained features are input into a Deep Neural Network (DNN), and parameter learning and model optimization are conducted through joint training. …”
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Optimization design of unloading mechanism for intelligent cleaning robots based on Adams by LIN Xinqiang

“…ObjectiveIn order to achieve the capability of whole process unmanned operation of the Robo-Sweep intelligent cleaning robot, it is necessary to develop a set of unloading mechanisms that meet various needs.MethodsFirstly, according to the overall design scheme of the whole machine, the preliminary design of the unloading mechanism was carried out through the graphical method. …”
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The Application of Kernel Ridge Regression for the Improvement of a Sensing Interferometric System by Ana Dinora Guzman-Chavez, Everardo Vargas-Rodriguez

“…In this work, it is shown that Kernel Ridge Regression (KRR), which is a machine learning method, can be applied to improve the range of measurement of multilayer interferometric sensors. …”
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Identification of Writing Strategies in Educational Assessments with an Unsupervised Learning Measurement Framework by Cheng Tang, Jiawei Xiong, George Engelhard

“…This study proposes a framework that leverages natural language processing and unsupervised machine learning techniques to measure, identify, and classify examinees’ writing strategies. …”
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Sucker rod straightness measurement method based on probability statistics of edge point detection by Li Zhu, Yihua Kang

“…Abstract Straightness is the basic measurement parameter in machining, and the traditional straightness measurement methods such as light gap method, table method, et al., have extremely low measurement efficiency and cannot achieve online real-time high-precision detection. …”
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Mechanochemical synthesis of AlCoCrFeNi powders via high-energy ball milling by Е.Е. Камбаров, А.Б. Кенесбеков, Ж.Б. Сагдолдина, Д.Б. Буйткенов

“…A preliminary mathematical calculation of the physical parameter responsible for the phase stability of the solid solution valence electron concentration (VEC) showed that the fusion of this system should form the FCC phase. …”
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Physical and Mechanical Properties of Deep Oceanic Sediments Cored from the Bottom of Challenger Deep, Mariana Trench by Xu Dai, Tao Xu, Jian Chen

“…Besides high water content, high porosity, high liquid limit, high plasticity, high consolidation coefficient, low compressive modulus, low shear strength, low density, and low specific gravity, the deep-sea mining machine may slip and subside. This research can improve the understanding of the deep-sea sedimentary environment of the Challenger Deep in the southwestern part of the Mariana Trench and provide an essential reference for the parameter calibration as well as the basis for walking-characteristic study and optimization design of the deep-sea mining vehicle.…”
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AI-BASED FIELD-ORIENTED CONTROL FOR INDUCTION MOTORS by Elmehdi Benmalek, Marouane Rayyam, Ayoub Gege, Omar Ennasiri, Adil Ezzaidi

“…RL is a machine learning approach that is model-free which can adapt to the variations and disturbances. …”
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Accelerated Multiobjective Calibration of Fused Deposition Modeling 3D Printers Using Multitask Bayesian Optimization and Computer Vision by Graig S. Ganitano, Benji Maruyama, Gilbert L. Peterson

“…Proper process parameter calibration is critical to the success of fused deposition modeling (FDM) three‐dimensional (3D) printing, but is time‐consuming and requires expertise. …”
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Wheel Tread Dynamic Detection Benchmark Positioning Method Based on Iterative Reweighted Least-squares Line Fitting by LI Miaocheng, WANG Junping, SHEN Yunbo, YOU Yong, DAI Bowang, LAN Qiangqiang

“…Under the dynamic tilt condition, the experimental man-machine comparison deviations of flange height and thickness based on IRLS-LF positioning results are ±0.1mm and ±0.2mm respectively, and the both deviation range widths based on LSLF positioning results and fixed-parameter algorithm positioning results are about 0.8 mm. …”
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TransUNet Image 3D Reconstruction with Hyperparameter Optimization by Xiaofang Wang, Zhihao Luo, Mingrui Gou, Kerui Mao, Liang Zhou

“…The method employs Restricted Boltzmann Machine (RBM) for depth prediction and an optimized ant colony algorithm for network parameter optimization. …”
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TO EVALUATE THE DYNAMIC DUCTILE FRACTURE OF PIPELINE STEELS BY USING INSTRUMENTED DROP WEIGHT TEAR TEST by FANG Jian, SHEN Wei, WANG Lei

“…As to monitor the crack behavior after crack initiation directly from an instrument load-displacement curve,the linear correlation between the limit load and the square of remaining ligament width has been confirmed by applying a huge 40 k J instrumented pendulum machine onto standard pressed-notch API X80 DWTT specimens and employing key curve method,which also provides an experimental way to determine the material based parameter of A*σf,required by other CTOACestimation algorithm. …”
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