A Novel Tree Model-based DNN to Achieve a~High-Resolution DOA Estimation via Massive MIMO Receive Array by Y. Li, F. Shu, Y. Song, J. Wang

“…To satisfy the high-resolution requirements of direction-of-arrival (DOA) estimation, conventional deep neural network (DNN)-based methods using grid idea need to significantly increase the number of output classifications and also produce a huge high model complexity. …”
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Comparative analysis of impact of classification algorithms on security and performance bug reports by Said Maryyam, Bin Faiz Rizwan, Aljaidi Mohammad, Alshammari Muteb

“…The aim of this research is to compare and analyze the prediction accuracy of machine learning algorithms, i.e., Artificial neural network (ANN), Support vector machine (SVM), Naïve Bayes (NB), Decision tree (DT), Logistic regression (LR), and K-nearest neighbor (KNN) to identify security and performance bugs from the bug repository. …”
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Calculation Method of Downstream Water Level in Non-Spilling Periods of Hydropower Stations Based on Decision Tree Classification and Multiple Linear Regression by LI Yinghai, HE Liangzhe, ZHANG Hairong, NIE Panpan, QIN Hui, YANG Qingyu, GUO Jiali

“…This method first employs the classification and regression tree (CART) algorithm, using long-series measured data from hydropower stations to establish decision tree classification rules and classify data of different operation working conditions. …”
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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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An Object Detection Algorithm for Orchard Vehicles Based on AGO-PointPillars by Pengyu Ren, Xuyun Qiu, Qi Gao, Yumin Song

“…Finally, we establish an orchard object detection dataset and validate the proposed algorithm. The results show that, compared to the PointPillars, the AGO-PointPillars proposed in this study has an average detection accuracy improvement of 4.64% for typical orchard objects such as potholes and trees, which can prove the reliability of our algorithm.…”
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Adaptive Algorithm Recommendation and Application of Learning Resources in English Fragmented Reading by Jinyu Cheng, Hong Wang

“…At the same time, to make the learning resources meet the characteristics of fragmented learning time and space, the English Level 4 reading resources are reasonably designed and segmented to adapt to the needs of learners’ mobile fragmented learning. Then, combined with machine learning algorithms, an adaptive recommendation model of learning resources in English fragmented reading is constructed. …”
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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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Evaluating Machine Learning Algorithms for Financial Fraud Detection: Insights from Indonesia by Cheng-Wen Lee, Mao-Wen Fu, Chin-Chuan Wang, Muh. Irfandy Azis

“…The study utilized Multiple Linear Regression along with advanced classification algorithms such as Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, and Random Forest, to detect financial statement fraud. …”
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Performance of Machine Learning Algorithms on Imbalanced Sentiment Datasets Without Balancing Techniques by Dina Wulan Yekti rahayu, Khothibul Umam, Maya Rini Handayani

“…This study explores the performance of five sentiment classification algorithms—Naïve Bayes, Logistic Regression, Support Vector Machine, Decision Tree, and Random Forest—on an imbalanced sentiment dataset, with the SMOTE technique applied as a comparison. …”
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IMPLEMENTATION OF DYNAMIC AND FAST MINING ALGORITHMS ON INCREMENTAL DATASETS TO DISCOVER QUALITATIVE RULES by Pannangi Naresh, R. Suguna

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Analisis Perbandingan Metode Regresi Linier, Random Forest Regression dan Gradient Boosted Trees Regression Method untuk Prediksi Harga Rumah by Evita Fitri

“…The purpose of this study is to carry out a comparative analysis of the prediction results of house prices with several Machine Learning algorithms consist of Linear Regression, Random Forest Regression and Gradient Boosted Trees Regression. …”
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Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models? by P. Sun, P. B. Holden, H. J. B. Birks, H. J. B. Birks

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Does the implementation of Automatic Individual Tree Crown Delineation (ITCD) impact the early detection of bark beetle (BB) infestation in Norway spruce forests? by S. Bijou, L. Kupková, L. Červená, J. Lysák

“…While UAV imagery offers high-resolution data, selecting appropriate crown pixels to detect subtle spectral changes during early BB infestation stages is still a challenge that needs further investigation. This study examines the impact of automatic Individual Tree Crown Delineation (ITCD) methods in detecting early-stage BB infestations, particularly during the green-to-yellow stage. …”
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A Data Mining Approach to Consumers’ Choice of Retail Market: The Case of Urban Retail Markets in Iran by H. Hashemzadeh, N. Yousefian, S. Esfandiari Bahraseman, A. Karbasi, A. Firoozzare

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Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users by Christopher Meaney, Xuesong Wang, Jun Guan, Therese A. Stukel

“…Hyper-parameter tuning using any HPO algorithm/sampler improved model discrimination (AUC=0.84), resulted in models with near perfect calibration, and consistently identified features predictive of high-need high-cost health care users. …”
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PhyloFunc: phylogeny-informed functional distance as a new ecological metric for metaproteomic data analysis by Luman Wang, Caitlin M. A. Simopoulos, Joeselle M. Serrana, Zhibin Ning, Yutong Li, Boyan Sun, Jinhui Yuan, Daniel Figeys, Leyuan Li

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Application of Ontology Matching Algorithm Based on Linguistic Features in English Pronunciation Quality Evaluation by Shan Zhu

“…This paper proposes a decision tree structure, which is similar to the overall scoring process of raters, and uses the Interactive Dicremiser version 3 (ID3) algorithm to build a comprehensive evaluation decision tree for pitch, rhythm, intonation, speech rate, and emotion indicators. …”
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Distributed denial-of-service (DDOS) attack detection using supervised machine learning algorithms by S. Abiramasundari, V. Ramaswamy

“…The CICIDS2018, CICIDS2017, and CICDDoS-2019 datasets are used to evaluate the performances of ML algorithms. Various performance metrics of these algorithms are studied and compared to find the best algorithm that yields the highest accuracy. …”
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Research on Spread Spectrum Codes Optimized by Sparrow Search Algorithm and Extreme Gradient Boosting by LIANG Zhiru, BIAN Dongming, ZHANG Gengxin

“…However, in non-cooperative communication scenarios, detecting DSSS signals, estimating DSSS signal parameters, and even intercepting information are all issues that need to be considered. In DSSS, correctly identifying the spread spectrum sequence used is an important prerequisite for correcting despreading. …”
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Multiobjective Multicast DSR Algorithm for Routing in Mobile Networks with Cost, Delay, and Hop Count by Hamdy H. El-Sayed, A. Younes, Fahad A. Alghamdi

“…Tremendous evaluation of wireless mobile communication needs more efficient algorithms for communication systems. …”
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