Statistical mechanics of dynamical system identification by Andrei A. Klishin, Joseph Bakarji, J. Nathan Kutz, Krithika Manohar

“…To establish this analogy, we define the hyperparameter optimization procedure as a two-level Bayesian inference problem that separates variable selection from coefficient inference and enables the computation of the posterior parameter distribution in closed form. …”
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APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS by Karin Joan, Robyn Irawan, Benny Yong

“…Multi-Output Machine Learning is an advancement of traditional machine learning, designed to predict multiple output variables simultaneously while considering the relationships between these output variables. …”
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A New Noninterior Continuation Method for Solving a System of Equalities and Inequalities by Jianguang Zhu, Binbin Hao

“…By using slack variables and minimum function, we first reformulate the system of equalities and inequalities as a system of nonsmooth equations, and, using smoothing technique, we construct the smooth operator. …”
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Downscaling of Soil Moisture Map using Sentinel Radar Satellite Images and Distribution Analysis in the West of Iran by Seyed Hossein Mirmosavi, kohzad Raispour, Muhammad Kamangar

“…Conclusion The results of this study with respect to the correlation coefficient of 0.5012 with real data and high spatial resolution of the output map showed the efficiency of using different bands of radar images in estimating surface moisture. …”
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Designing a supply chain resilience assessment model with the approach of NDEA(case of study: government hospitals of Yazd province) by Mohsen Shafiei Nikabadi, Fereshteh Bahrami

“…Therefore, in order to maintain the basic functions and quickly return the hospital to its original state, the resilience of the hospital is important (Mohammed Hosseini Issini, 2019), which calls attention to the necessity of availability and efficiency of hospitals. …”
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Research on Constraint Processing Method of High-dimensional Optimization Operation Problem of Cascade Reservoirs by Zhongzheng HE, Shuliang LI, Wei HUANG, Feng YAN, Jisi FU, bin XIONG

“…The intelligent optimization algorithm is a multidimensional linkage random search, which boasts a vast optimization space but suffers from low optimization efficiency. Therefore, this study introduces a constraint processing approach that integrates a penalty function with nested DPSA–POA and intelligent algorithms and applies it to the optimal flood control operation problem of cascade reservoirs in the middle reaches of the Ganjiang River, with decision variables extending to 2196 dimensions. …”
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Bivariate Epanechnikov-exponential distribution: statistical properties, reliability measures, and applications to computer science data by H. M. Barakat, M. A. Alawady, I. A. Husseiny, M. Nagy, A. H. Mansi, M. O. Mohamed

“…The statistical properties of the EP-EX-FGM model are examined, including product moments, coefficient of correlation between the internal variables, moment generating function, conditional distribution, concomitants of order statistics (OSs), mean residual life function, and vitality function. …”
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ANALYSIS OF CONTACT LOADS CONCENTRATION IN PRESSURE COUPLINGS OF THIN-WALL COMPONENTS by S. V. Shishkin

“…Deviations of the shape of the contact surfaces from the straightness are taken into account by its respective pressure coupling function. The analysis of the findings suggests that the concentration coefficient value slumps as the contact compliance coefficient of the borderline layer increases. …”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…The dataset included 768 instances with nine attributes, where the target variable indicated whether a patient tested positive for diabetes. …”
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Respiratory Muscle Strength as a Predictor of VO2max and Aerobic Endurance in Competitive Athletes by Gökhan Deliceoğlu, Banu Kabak, Veli O. Çakır, Halil İbrahim Ceylan, Muntean Raul-Ioan, Dan Iulian Alexe, Valentina Stefanica

“…Previous research has elucidated the complex interactions between respiratory and skeletal muscles during exercise, highlighting the critical role of efficient respiration in maximizing athletic performance. …”
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Optimum Design of RC Beams Strengthened with Externally Bonded FRP Using Pattern Search by Noor Mohammed Sheet, Baraa J. M. AL-Eliwi, Rabi M. Najem

“…The design process involved an objective function that represents the cost function of the optimum solution and design variables that define the optimum dimensions of the beam and FRP material, such as beam width, effective beam depth, FRP strip thickness, FRP strips spacing, and FRP strip width, according to the design constraints of the ACI 440-2R-17 code. …”
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Enhanced Stability and Control of Solar Powered EV Charging Stations Using Disturbance Observer-Based Adaptive Sliding Mode Control for DC Voltage Stabilization by Surabhi Bagherwal, Subhasish Mahapatra

“…To address the chattering issue, a barrier function based SMC (BFSMC) approach is proposed. The distinctive aspects of this BFSM control approach is its capability to stabilize the designed sliding variable to a predefined neighbourhood around the origin within a limited duration, eliminating the need for prior understanding of the maximum limit of the lumped disturbance. …”
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Comparative Analysis of ANFIS and State-ANFIS for Forecasting Cooking Oil Prices Based on Processed Palm Oil Yield (Crude Palm Oil) by Brodjol Sutijo Suprih Ulama, Fausania Hibatullah, Mochammad Reza Habibi, null Makkulau

“…Our analysis underscores S-ANFIS’s superiority over ANFIS, particularly with Gaussian membership functions, as it reduces RMSE and MAPE values by half while requiring fewer nodes, thereby improving computational efficiency. …”
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Application of the Salp Swarm Algorithm to Optimal Design of Tuned Inductive Choke by Łukasz Knypiński, Milena Kurzawa, Rafał Wojciechowski, Michał Gwóźdź

“…A lumped-parameters model of a tuned inductive choke was developed, with the device’s structure described by three design variables. As an optimality criterion, the multi-objective compromise function was adopted. …”
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Analisis Kualitas Website Balai Besar Taman Nasional Gunung Gede Pangranggo (BBTNGGP) menggunakan Metode Webqual 4.0 by Muhammad Syahid Qadhafi, Atit Pertiwi

“…The results of the analysis of the quality of this website concluded that the variable usability and information quality had a good value compared to the variable service interaction quality. …”
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Optimization of Sparse Concentric Ring Arrays for Low Sidelobe by Kesong Chen, Yafei Li, Jiajia Shi

“…The MGA uses real number to code the optimization variable, and it reduces the complexity of coding and improves the search efficiency. …”
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Deep Multi-Component Neural Network Architecture by Chafik Boulealam, Hajar Filali, Jamal Riffi, Adnane Mohamed Mahraz, Hamid Tairi

“…The architecture’s efficiency is further demonstrated by its reduced trainable parameters and robust handling of multimodal and variable-length inputs, making it a versatile solution for classification tasks.…”
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Promoting Social Participation in the Primary Care Field: An Ecological Study on the Potential Reduction of Multimorbidity Prevalence by Ryota Takahashi, Tadao Okada, Kazushige Ide, Taishi Tsuji, Katsunori Kondo

“…Multiple regression analysis was performed with MP as objective variable; social participation or household income were explanatory variables, and education, population density, and health check-ups were adjustment variables. …”
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AESware: Developing AES-enabled low-power multicore processors leveraging open RISC-V cores with a shared lightweight AES accelerator by Eunjin Choi, Jina Park, Kyuseung Han, Woojoo Lee

“…AESware supports variable key lengths and ensures minimal power consumption with a compact design. …”
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Autonomous obstacle avoidance of underground coal mine transport robots based on intrinsic motivation reinforcement learning algorithm by ZHAO Kebao, LI Lingfeng, CHEN Zhuo, HAN Jun, YIN Rui

“…Existing robot obstacle avoidance methods mostly rely on preset rules or external reward signals, making it difficult to adapt to the complex and variable underground environment in coal mines. To achieve autonomous and efficient obstacle avoidance for underground coal mine transport robots, an autonomous obstacle avoidance method for underground coal mine transport robot based on Intrinsic Motivation Reinforcement Learning (IM-RL) algorithm was proposed. …”
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