Enhanced securities investment strategy using ISSA–SVM: a hybrid model combining adaptive moving average, support vector machine, and multi-strategy sparrow search algorithm for im... by Wei Ni, Qingqing Chen, Xiaochen Guo, Yanan Liu

“…This study proposes a novel hybrid strategy, ISSA–SVM, that combines Adaptive Moving Average (AMA), Support Vector Machine (SVM), and an Improved Sparrow Search Algorithm (ISSA) to enhance CTA model performance in securities investment. …”
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Response estimation and system identification of dynamical systems via physics-informed neural networks by Marcus Haywood-Alexander, Giacomo Arcieri, Antonios Kamariotis, Eleni Chatzi

“…This study specifically investigates three key applications of PINNs: state estimation in systems with sparse sensing, joint state-parameter estimation, when both system response and parameters are unknown, and parameter estimation from full-field observation, within a Bayesian framework to quantify uncertainties. …”
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Consideration of the geomechanical state of a fractured porous reservoir in reservoir simulation modelling by Yurii A. Kashnikov, Denis V. Shustov, Sergei Yu. Yakimov

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Optimizing Solar Radiation Prediction Based on The Internet of Things Platform in Photovoltaic Power Plant by Neda Ashrafi Khozani, Maryam Mahmoudi, Shabnam Nasr Esfahani

“…The solar radiation value parameter is one of the most important parameters in determining the output power value of photovoltaic panels. …”
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What Influences Low-cost Sensor Data Calibration? - A Systematic Assessment of Algorithms, Duration, and Predictor Selection by Lu Liang, Jacob Daniels

“…This study comprehensively assessed ten widely used data techniques, namely AdaBoost, Bayesian ridge, gradient tree boosting, K-nearest neighbors, Lasso, multivariable linear regression, neural network, random forest, ridge regression, and support vector machine. We compared their performance using a standardized baseline dataset and their responses to various parameter combinations. …”
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Climate Adaptation Strategies for Maintaining Rice Grain Quality in Temperate Regions by Yvonne Fernando, Ben Ovenden, Nese Sreenivasulu, Vito Butardo

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MW-UNet: Multi-Scale Weighted Connection UNet for Identification and Classification of Non-Meteorological Clutter over Big Radar Data by Mengmeng Cui, Chen Zeng, Xiaolong Xu, Muhammad Bilal, Xiaoyu Xia

“…Additionally, the channel-focused feature fusion mechanism is able to analyze the deep latent features of the input parameters and suppress the useless features, so that only six polarization parameters are required as inputs. …”
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A novel method for power transformer fault diagnosis considering imbalanced data samples by Jun Chen, Yong Wang, Lingming Kong, Yilong Chen, Mianzhi Chen, Qian Cai, Gehao Sheng

“…Hyperparameter tuning is achieved through the Bayesian optimization algorithm to identify the model parameter set that maximizes test set accuracy.ResultsAnalysis of the transformer fault case library reveals that the model proposed in this paper reduces diagnostic time by nearly half compared to traditional machine learning diagnosis models. …”
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Citrus quality grading based on statistical complexity measurement and multifractal spectrum method by Cao Leping, Wen Zhiyuan

“…C(Y) and H(Y) were set as the features to identify fruit diseases and insect pests by machine recognition. The background and extracting boundary contour from the two projection images formed by navel orange fruits' stalk surface and side perpendicular were removed, and then perimeter-area fractal dimension was calculated. …”
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Perspectives and Tools in Liver Graft Assessment: A Transformative Era in Liver Transplantation by Kawthar Safi, Angelika Joanna Pawlicka, Bhaskar Pradhan, Jan Sobieraj, Andriy Zhylko, Marta Struga, Michał Grąt, Alicja Chrzanowska

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Influencing factors of cross screening rate and its intelligent prediction model by Lala ZHAO, Feng XU, Chenlong DUAN, Chenhao GUO, Wei WANG, Haishen JIANG, Jinpeng QIAO

“…Combined with particle swarm optimization (PSO), the hyper-parameter combination optimization of support vector machine, decision tree and random forest models is carried out to obtain the optimal parameter combination of the model and improve the prediction performance and generalization ability of the model. …”
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The fourth order flux observer with in‐loop filter for permanent magnet synchronous motor sensorless control by Ziwen Wang, Ciyong Luo, Xiaoshu Jia, Zihao Xing

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An influence of wall structure on acoustic pressure distribution in a operator’s cabin by S. Michałowski, B. Stolarski, Z. Dziechciowski

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Sustainable Cooling Strategies in End Milling of AISI H11 Steel Based on ANFIS Model by Arumugam Balasuadhakar, Sundaresan Thirumalai Kumaran, Saood Ali

“…The experimental framework is based on a Taguchi L36 orthogonal array, with key parameters including feed rate, cutting speed, cooling condition, and air pressure. …”
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Comparative Studies of the Properties of Copper Components: Conventional vs. Additive Manufacturing Technologies by Witold Malec, Joanna Kulasa, Anna Brudny, Anna Hury, Bartlomiej Adamczyk, Ryszard Rzepecki, Robert Sekula, Grzegorz Kmita, Andrzej Rybak

“…Same-sized components made in a conventional casting and subtractive method (machining) were used as a reference material. Comprehensive tests and the comparison of a wide range of parameters allowed us to determine that among the selected methods, printing using the DMLS technique allowed for obtaining arcing contact with mechanical and electrical parameters very similar to the reference element. …”
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Advanced MMC-Based Hydrostatic Bearings for Enhanced Linear Motion in Ultraprecision and Micromachining Applications by Ali Khaghani, Atanas Ivanov, Mina Mortazavi

“…This study investigates the impact of material selection on the performance of linear slideways in ultraprecision machines used for freeform surface machining. The primary objective is to address challenges related to load-bearing capacity and limited bandwidth in slow tool servo (STS) techniques. …”
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Software for developing digital twins of agricultural machinery working bodies by D. A. Mironov, D.  V. Popov, R. K. Rasulov, A. K. Lamm

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Concept of Developing a Gear Selection Tool for Improved Accuracy in Industrial Robotics by Muhammad Faisal Yaqoob, Christian Gollee, Christer-Clifford Schenke, Steffen Ihlenfeldt

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Skew Logistic Distribution Applied as Activation Function in Artificial Neural Networks by Eder Silva Dos Santos, Altemir da Silva Braga, Ana Beatriz Alvarez, Thuanne Paixao

“…In recent years, Artificial Neural Networks (ANNs) have stood out among machine learning algorithms in many applications, such as image and video pattern recognition. …”
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Combined Impacts of Temperature, Sea Ice Coverage, and Mixing Ratios of Sea Spray and Dust on Cloud Phase Over the Arctic and Southern Oceans by Barbara Dietel, Hendrik Andersen, Jan Cermak, Philip Stier, Corinna Hoose

“…Abstract We analyze the importance of cloud top temperature, dust aerosol, sea salt aerosol, and sea ice cover for the thermodynamic phase of low‐level, mid‐level, and mid to low‐level clouds observed by CloudSat/CALIPSO over the Arctic and the Southern Ocean using an explainable machine learning technique. As expected, the cloud top temperature is found to be the most important parameter for determining cloud phase. …”
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