Extraction of exact symbolic stationary probability formulas for Markov chains in finite space with application to production lines. part II: unveiling accurate formulas for very s... by Konstantinos S. Boulas, Georgios D. Dounias, Chrissoleon T. Papadopoulos

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Knowledge Acquisition for the Stunting Prevention Expert System (SIPENTING) using Decision Tree and Grid Search by Azhar Basir, Fitri Ayuning Tyas

“…The system is Android-based and aims to help pregnant women better understand their nutritional needs. Testing and validation results show that the Decision Tree model achieved an accuracy of 86.3%.…”
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Application of Data Mining Techniques on Tourist Expenses in Malaysia by Miao Cai, Tan Shi An

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Efficient Fault Diagnosis of Elevator Cabin Door Drives Using Machine Learning with Data Reduction for Reliable Transmission by Jakub Gęca, Dariusz Czerwiński, Bartosz Drzymała, Krzysztof Kolano

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Measurement of spatial heterogeneity in street restorative perceptions and street refinement design by Yalun Lei, Qingqing Li, Jingwen Tian, Jia Hu, Jixiang Jiang

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A Novel LSTM Architecture for Automatic Modulation Recognition: Comparative Analysis With Conventional Machine Learning and RNN-Based Approaches by Sam Ansari, Soliman Mahmoud, Sohaib Majzoub, Eqab Almajali, Anwar Jarndal, Talal Bonny

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Spilt Tensile Strength of Fiber-Reinforced Recycled Aggregate Concrete Simulation Employing Tunned Random Forests Trees by Xiao Chen, Chen Xi, Min Xiao, Lang Wu

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Effective Breast Cancer Classification Using Deep MLP, Feature-Fused Autoencoder and Weight-Tuned Decision Tree by Nagham Rasheed Hameed Alsaedi, Mehmet Fatih Akay

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Development and validation of a decision tree model for prediction of insomnia risk among ischemic stroke convalescence patients by Xuefeng Sun, Zilin Wang, Yuqing Song, Deyu Cong, Shu Sun, Xinye Zhang, Ye Zhang, Hongshi Zhang

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Big Data Analysis of Lung Cancer Dataset Using Classification by Tannady Hendy, Fernandes Andry Johanes, Susanto William, Tannady Tan Henny, Bin Rakiman Umol Syamsyul

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Securing fruit trees future: AI-driven early warning and predictive systems for abiotic stress in changing climate by Muhammad Ahtasham Mushtaq, Muhammad Ateeq, Muhammad Ikram, Shariq Mahmood Alam, Muhammad Mohsin Kaleem, Muhammad Atiq Ashraf, Muhammad Asim, Khalid F. Almutairi, Mahmoud F. Seleiman, Fareeha Shireen

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Aerospace Equipment Fault Diagnosis Method Based on Fuzzy Fault Tree Analysis and Interpretable Interval Belief Rule Base by Mingxian Long, Hailong Zhu, Guangling Zhang, Wei He

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Generative design optimization of tree distribution for enhanced thermal comfort in communal spaces with special reference to hot arid climates by Ahmed Maged, Aly Abdelalim, Abdelaziz Farouk A. Mohamed

“…Secondly, a generative design tool with a Dynamo evolutionary algorithm is utilized to optimize the tree distribution across the communal areas of these three spaces considering the current built environment. …”
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Advances in the Automated Identification of Individual Tree Species: A Systematic Review of Drone- and AI-Based Methods in Forest Environments by Ricardo Abreu-Dias, Juan M. Santos-Gago, Fernando Martín-Rodríguez, Luis M. Álvarez-Sabucedo

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Comparing the potential of tree-based and area-based forest height metrics for aboveground biomass estimation in complex forest landscapes by Weiyan Liu, Yuling Chen, Haitao Yang, Guangcai Xu, Shiyu Yan, Lingjun Li, Ling Chen, Qinghua Guo

“…The results indicate the following: (1) Tree-based metrics that align more closely with forestry definitions demonstrate higher predictive accuracy than area-based metrics, particularly Lorey’s mean height and top height. (2) Among machine learning models, CatBoost, which incorporates Lorey’s mean height, achieve the highest accuracy (R2 = 0.688, relative RMSE = 41.85 %, MAE = 18.15 Mg/ha). (3) While area-based metrics are widely used in large-scale assessments due to their scalability, our results underscore the superior precision of tree-based metrics in AGB estimations, showing an 11.0 % to 23.1 % improvement of R2 over the area-based metrics. (4) Regional variations across Beijing further highlight the need to tailor metric selection to specific landscape and modeling objectives. …”
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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning by Lucijano Berus, Jernej Hernavs, David Potocnik, Kristijan Sket, Mirko Ficko

“…Different machine learning algorithms, such as Random Forest (RF), k-nearest neighbors (k-NN), and Decision Trees (DT), were used for predictive modeling. …”
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Preparation of land subsidence susceptibility map using machine learning methods based on decision tree (case study: Isfahan–Borkhar) by Negar Ghasemi, Iman Khosravi, Ali Bahrami

“…All input datasets (as input factors for machine learning algorithms) were co-registered to match the resolution of the InSAR-derived maps (100 meters).Machine learning algorithms: Three machine learning algorithms including decision tree (DT), random forest (RF) and extreme gradient boosting (XGBoost) were tested. …”
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The Concept Design of Rice Quality Detection System Using Model-Based System Engineering Approach by Purwa Tri Cahyana, Titi Candra Sunarti, Erliza Noor, Hartrisari Hardjomidjojo, Noer Laily

“…Moreover, machine learning techniques were used to simulate rice quality data analysis using the decision tree classification with the Iterative Dichotomizer 3 (ID3) algorithm. …”
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Machine Learning in the National Economy by Azamjon A. Usmonov

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Potential impacts of future climate on twelve key multipurpose tree species in Benin: Insights from species distribution modeling for biodiversity conservation by Sèdoami Flora Dogbo, Kolawolé Valère Salako, Gafarou Agoundé, Kangbéni Dimobe, Adjo Estelle Geneviève Adiko, Jens Gebauer, Constant Yves Adou Yao, Romain Glèlè Kakaï

“…This study modeled the future suitable habitats of twelve key multipurpose tree species (MPTS) in Benin under two climate scenarios, Shared Socioeconomic Pathways 245 (SSP245) and 585 (SSP585), based on a 2070 horizon. …”
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