Deep-Learning-Based Land Cover Mapping in Franciacorta Wine Growing Area by Girma Tariku, Isabella Ghiglieno, Andres Sanchez Morchio, Luca Facciano, Celine Birolleau, Anna Simonetto, Ivan Serina, Gianni Gilioli

“…Through meticulous data acquisition, preprocessing, model selection, and evaluation, we demonstrate the effectiveness of these techniques in accurately identifying land cover classes. …”
Get full text

Machine Learning Model for Processing Aerospace Images of the Earthʼs Surface by T. F. Starovoitova, I. A. Starovoitov

“…The methodology for creating a machine learning model includes defining the goals and objectives of the model, selecting an appropriate learning algorithm (in this case, neural networks), collecting and preparing a data set, tuning the model, and testing on a test data set. …”
Get full text

The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee by Diding Suhandy, Meinilwita Yulia

“…Several preprocessing methods were tested and the results show that most of the preprocessing spectra were effective in improving the quality of calibration models with the best PLS calibration model selected for Savitzky-Golay smoothing spectra which had the lowest RMSECV (0.039) and highest RPDcal value (4.64). …”
Get full text

Entrepreneurial determinants of Moroccan business failure: entrepreneurial behaviors and attitudes by Youssef Zizi, Amine Jamali-Alaoui, Badreddine El Goumi

“…Applying variable selection techniques and models selection criteria, such as AIC and BIC, the main results indicate that the model composed of variables related to entrepreneurial behavior and attitudes variables, specifically fear of failure rate, perceived capabilities rate, and perceived opportunities rate, better explains bankruptcy rate. …”
Get full text

Description-based Post-hoc Explanation for Twitter List Recommendations by Havva Alizadeh Noughabi, Behshid Behkamal, Mohsen Kahani

“…In this paper, we propose an explanation model to provide relevant and informative explanations for recommended Lists by automatically generating descriptions for Twitter Lists. The model selects the most informative tweets from a List as its description to inform users more with the recommended List that positively contributes to the user experience. …”
Get full text

NOx, Soot, and Fuel Consumption Predictions under Transient Operating Cycle for Common Rail High Power Density Diesel Engines by N. H. Walke, M. R. Nandgaonkar, N. V. Marathe

“…Hence, in this work, a 0D comprehensive predictive model has been formulated with selection and coupling of appropriate combustion and emissions models to engine cycle models. Selected combustion and emissions models are further modified to improve their prediction accuracy in the full operating zone. …”
Get full text

The Construction of Corporate Financial Management Risk Model Based on XGBoost Algorithm by Rongyuan Qin

“…The research results show that the XGBoost model selected in this paper has high reliability in predicting the financial risk assessment of enterprises, and the prediction errors are all within 3%. …”
Get full text

Sensitivity Evaluation of AP1000 Nuclear Power Plant Best Estimation Model by Hao Shi, Qi Cai, Yuqing Chen

“…Based on the best estimate thermal-hydraulic system code RELAP5/MOD3.2, sensitivity analysis has been performed on core partition methods, parameters, and model selections in AP1000 Nuclear Power Plant, like the core channel number, pressurizer node number, feedwater temperature, and so forth. …”
Get full text

A Comparative CFD Study on Simulating Flameless Oxy-Fuel Combustion in a Pilot-Scale Furnace by Mersedeh Ghadamgahi, Patrik Ölund, Tomas Ekman, Nils Andersson, Pär Jönsson

“…This provides a recommendation for model selections in further studies on flameless oxy-fuel combustion.…”
Get full text

Methods of Bank Valuation in the Age of Globalization by A. Karminsky, E. Frolova

“…The paper identifies five main factors that significantly influence valuation models selection and building: funding, liquidity, risks, exogenous factors and the capital cushion. …”
Get full text

Comparison of blockchain vs. centralised IT infrastructure costs for food traceability: a Thai broiler supply chain case study by Suchit Pongnumkul, Patcharawadee Ittipornpaisarn, Suporn Pongnumkul

“…We analysed both centralised and blockchain IT models, selecting 13 deployment scenarios for comparison. …”
Get full text

Geometrical Distances of Extragalactic Binaries through Spectroastrometry by Yu-Yang Songsheng, Jian-Min Wang, Yuan Cao, XueFei Chen, JianPing Xiong, Zhi-Xiang Zhang, Rong-Gen Cai

“…As a geometric method based on the simplest dynamics, it is independent of empirical calibration, and the systematics caused by model selections can be tested using nearby binaries with known distances. …”
Get full text

An optimization approach for improving steam production of heat recovery steam generator by Awsan Mohammed, Moath Al-Mansour, Ahmed M. Ghaithan, Adel Alshibani

“…The results also showed that the proposed model selects and provides the optimal HRSG parameter values to maximize steam production within the relevant defined constraints.…”
Get full text

Explainable AI-Enhanced Human Activity Recognition for Human–Robot Collaboration in Agriculture by Lefteris Benos, Dimitrios Tsaopoulos, Aristotelis C. Tagarakis, Dimitrios Kateris, Patrizia Busato, Dionysis Bochtis

“…The XGBoost-based model, selected mainly for allowing an in-depth analysis of feature contributions by considerably reducing the complexity of calculations, demonstrated strong performance in HAR. …”
Get full text

Computer‐Aided High Tibial Osteotomy—A Comparative Study of Commonly Used 3D Printing Technology and Navigation Application by Elvis Chun‐Sing Chui, Kyle Ka‐Kwan Mak, Randy Hin‐Ting Ng, Ericsson Chun‐Hai Fung, Mei‐Shuen Chan, Kai Yue, Lawrence Chun‐Man Lau, Clifford Long‐Fung Chan, Edmond Wing‐Fung Yau, Wei Zhao, Xiuyun Su, Jin Zhang, Jianglong Xu, Hongxun Sang, Guoxian Pei, Louis Wing‐Hoi Cheung, Sheung‐Wai Law, Michael Tim‐Yun Ong, Patrick Shu‐Hang Yung

“…This study compared different 3D printing techniques (fused deposition modeling, selective laser sintering, and direct metal laser sintering) and a navigation system for their suitability in assisting HTO surgeries. …”
Get full text

CDR-Detector: a chronic disease risk prediction model combining pre-training with deep reinforcement learning by Shaofu Lin, Shiwei Zhou, Han Jiao, Mengzhen Wang, Haokang Yan, Peng Dou, Jianhui Chen

“…In order to solve the problem of data imbalance, a dual experience replay strategy is realized to help the model select representative data samples and accelerate model convergence on the imbalanced EHR data. …”
Get full text

Predicting Screening Efficiency of Probability Screens Using KPCA-GRNN with WP-EE Feature Reconstruction by Qingtang Chen, Yijian Huang

“…Following the extraction of two core principal components, model parameters when KPCA’s σ2 = 0.85, the optimal parameter of GRNN model Spread = 0.051, and the optimal number of training samples N = 19, the average prediction error is 1.434%, the minimum prediction error reaching 0.708%, the minimum root mean square error reaching 0.836% and Pearson correlation coefficient marking the closest to 1, these result all representing the optimum achievable values. The budget model selects the optimal parameter combination scheme for the system.…”
Get full text

Effectiveness of pre-employment card policy on employment transition during covid-19: evidence from Indonesian dual labor market by Beni Teguh Gunawan, El Bram Apriyanto, Hennigusnia Hennigusnia, Ivan Lilin Suryono, Ardhian Kurniawati

“…To analyze employment transitions, this research employs a multinomial logit model, selected for its ability to estimate the probability of multiple, categorical employment outcomes, making it especially suitable for evaluating the diverse pathways individuals might take from unemployment to formal or informal employment, and from informal to formal sectors. …”
Get full text

Generalization of stochastic mortality models to improve mortality prediction in life insurance and pension funds by Shirin Shoaee, Mohammad Mehdi Gholi Keshmarzi

“…The purpose of this study is to generalize static stochastic mortality models to dynamic stochastic mortality models and to predict mortality rates based on the generalization of stochastic mortality models by the Cox-Ingersoll-Ross (CIR) process and to compare the results with each other.Methodology: In this research, two suggestions are presented: the first idea is to provide a dynamic correction method to increase the prediction accuracy using the CIR process and the second idea is to examine the out-of-sample validation method.Findings: In this study, using the out-of-sample validation method, the force of mortality from the best models selected from the two famous mortality model families (Lee-Carter and Cairns, Blake and Dowd (CBD)) is compared with the results of the generalized model. …”
Get full text

Establishing a preoperative predictive model for gallbladder adenoma and cholesterol polyps based on machine learning: a multicentre retrospective study by Yubing Wang, Chao Qu, Jiange Zeng, Yumin Jiang, Ruitao Sun, Changlei Li, Jian Li, Chengzhi Xing, Bin Tan, Kui Liu, Qing Liu, Dianpeng Zhao, Jingyu Cao, Weiyu Hu

“…Results Among the 110 combination predictive models, the Support Vector Machine + Random Forest (SVM + RF) model demonstrated the highest AUC values of 0.972 and 0.922 in the training and internal validation sets, respectively, indicating an optimal predictive performance. The model-selected features included gallbladder wall thickness, polyp size, polyp echo, and pedicle. …”
Get full text