Search Results - art AND random tree algorithm*

Forecasting vapor pressure deficit for agricultural water management using machine learning in semi-arid environments by Elbeltagi, Ahmed, Srivastava, Aman, Deng, Jinsong, Li, Zhibin, Raza, Ali, Khadke, Leena, Yu, Zhoulu, El-Rawy, Mustafa

“… (ART), Random SubSpace (RSS), Random Forest (RF), Reduced Error Pruning Tree (REPTree), and Quinlan's M5 algorithm…”
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Perfect prosthetic heart valve: generative design with machine learning, modeling, and optimization by Danilov, Viacheslav V., Klyshnikov, Kirill Y., Onishenko, Pavel S., Proutski, Alex, Gankin, Yuriy, Melgani, Farid, Ovcharenko, Evgeny A.

“… For optimal design, we investigate six state-of-the-art optimization algorithms, including Random Search, Tree-structured Parzen Estimator, CMA-ES-based algorithm, Nondominated Sorting…”
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Multivariate Modelling of the Trace Element Chemistry of Arsenopyrite from Gold Deposits Using Higher-Dimensional Algebras by Thiruvengadam, Sudharsan, Murphy, Matthew Edmund, Tan, Jei Shian, Watling, Roger John, Stewart, James Ian, Miller, Karol

“…In geochemistry, the elevated concentrations of certain elements in rock or mineral samples are used for the assessment of a mineralising system’s important…”
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Mastering the game of Go with deep neural networks and tree search by Silver, David, Huang, Aja, Maddison, Chris J., Guez, Arthur, Sifre, Laurent, van den Driessche, George, Schrittwieser, Julian, Antonoglou, Ioannis, Panneershelvam, Veda, Lanctot, Marc, Dieleman, Sander, Grewe, Dominik, Nham, John, Kalchbrenner, Nal, Sutskever, Ilya, Lillicrap, Timothy, Leach, Madeleine, Kavukcuoglu, Koray, Graepel, Thore, Hassabis, Demis

“… Without any lookahead search, the neural networks play Go at the level of state-of-the-art Monte Carlo tree search programs that simulate thousands of random games of self-play…”
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Hybrid feature selection framework for enhanced credit card fraud detection using machine learning models by Siam, Al Mahmud, Bhowmik, Pankaj, Uddin, Md Palash

“…), and random forest importance (RFI), each optimized for the dataset‘s characteristics. Pearson Correlation eliminates redundancy by removing…”
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Censoring weighted separate-and-conquer rule induction from survival data by Wróbel, Ł, Sikora, M

“…Rule induction is one of the major methods of machine learning. Rule-based models can be easily read and interpreted by humans, that makes them particularly…”
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Fault diagnosis based on extremely randomized trees in wireless sensor networks by Saeed, Umer, Jan, Sana Ullah, Lee, Young-Doo, Koo, Insoo

“… Most of the faults that commonly occur in WSN are considered: hardover, drift, spike, erratic, data-loss, stuck, and random fault…”
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Flood susceptibility modeling in Teesta River basin, Bangladesh using novel ensembles of bagging algorithms by Talukdar, Swapan, Ghose, Bonosri, Shahfahad, Salam, Roquia, Mahato, Susanta, Pham, Quoc Bao, Linh, Nguyen Thi Thuy, Costache, Romulus, Avand, Mohammadtaghi

“…The flooding in Bangladesh during monsoon season is very common and frequently happens. Consequently, people have been experiencing tremendous damage to…”
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Annotating mobile phone location data with activity purposes using machine learning algorithms by Liu, Feng, Janssens, Davy, Wets, Geert, Cools, Mario

“…► We annotate mobile phone location data using data mining techniques. ► The characteristics of underlying activity-travel behavior are also considered. ► A…”
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An empirical comparison of machine learning techniques for dam behaviour modelling by Salazar, F., Toledo, M.A., Oñate, E., Morán, R.

“…•A sensitivity analysis to the training set size was performed.•Machine learning tools mostly outperform HST, especially boosted regression trees…”
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Integrating feature engineering, genetic algorithm and tree-based machine learning methods to predict the post-accident disability status of construction workers by Koc, Kerim, Ekmekcioğlu, Ömer, Gurgun, Asli Pelin

“…: Random Forest, XGBoost, AdaBoost, and Extra Trees, as well as a state-of-the-art optimization method for hyperparameter tuning, Genetic Algorithm (GA…”
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MLSFDD: Machine-Learning-Based Smart Fire Detection Device for Precision Agriculture by Maity, Tapan, Nath Bhawani, Adi, Samanta, Jagannath, Saha, Prabir, Majumdar, Shubhankar, Srivastava, Gautam

“… The proposed MLSFDD has gathered data from agricultural crop fields through sensors and sensed data are analyzed using state-of-the-art ML algorithms such as random forest (RF…”
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An ensemble classification approach for cervical cancer prediction using behavioral risk factors by Ali, Md Shahin, Hossain, Md Maruf, Kona, Moutushi Akter, Nowrin, Kazi Rubaya, Islam, Md Khairul

“… Comparison with other state-of-the-art algorithms using several ML techniques, including support vector machine, decision tree, random forest…”
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R-Ensembler: A greedy rough set based ensemble attribute selection algorithm with kNN imputation for classification of medical data by Bania, Rubul Kumar, Halder, Anindya

“…•The proposed method is compared with five other state-of-the-art attribute selection methods…”
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Use of random forest algorithm to evaluate model-based EUI benchmarks from CBECS database by Kaskhedikar, Apoorva, Reddy, T. Agami, Runger, George

“…Evaluating the extent to which an individual building consumes energy in excess of its peers is the first step in initiating energy efficiency improvements…”
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Identifying Fake News written on Albanian language in social media using Naïve Bayes, SVM, Logistic Regression, Decision Tree and Random Forest algorithms by Hoti, Arber H., Hoti, Mergim H., Hoti, Hamdi, Salihu, Armend

“… Hence, this study aims to identify which algorithms classify in better form these fake news from different sources…”
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No more privacy Concern: A privacy-chain based homomorphic encryption scheme and statistical method for privacy preservation of user’s private and sensitive data by Sathish Kumar, G., Premalatha, K., Uma Maheshwari, G., Rajesh Kanna, P.

“…Internet giants collects a huge volume of data using the modern technologies and apply them to data mining for prediction and decision making in numerous…”
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Developing robust arsenic awareness prediction models using machine learning algorithms by Singh, Sushant K., Taylor, Robert W., Rahman, Mohammad Mahmudur, Pradhan, Biswajeet

“… First a logistic regression model was applied and its results compared with those produced by six state-of-the-art machine-learning…”
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Migraine headache (MH) classification using machine learning methods with data augmentation by Khan, Lal, Shahreen, Moudasra, Qazi, Atika, Jamil Ahmed Shah, Syed, Hussain, Sabir, Chang, Hsien-Tsung

“…Migraine headache, a prevalent and intricate neurovascular disease, presents significant challenges in its clinical identification. Existing techniques that…”
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Intelligent path planning for autonomous ground vehicles in dynamic environments utilizing adaptive Neuro-Fuzzy control by Ambuj, Machavaram, Rajendra

“… This study proposes a hybrid control strategy that integrates an improved A∗ algorithm for path planning with a Proportional-Integral-Derivative (PID…”
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