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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…In this research, a vision system algorithm has been developed to identify and locate base of young corn trees based upon robot vision technology, pattern recognition techniques, and knowledge-based decision theory. …”
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A Bio-Inspired Territorial Predator Scent Marking Algorithm in Software-Defined Data Center by Hacham S., Din N.M., Balasubramanian N.

Development of trees management system using radial basis function neural network for rain forecast by Auzani, Hasnul, Hashim, Khairusy Syakirin Has-Yun, Mohd Nazri, Farah Aniza

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Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman by Abdul Aziz, Maslina, Mustakim, Nurul Ain, Abdul Rahman, Shuzlina

“…The result indicated that the highest accuracy of 89.34% was achieved by the Random Tree algorithm, while the rule-based algorithm PART reached an accuracy of 87.56%. …”
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Removing impulse noise images by using decision tree algorithm by Sethu, Devika, Hasoon, Feras N., Hasson, Nebras N., Al-Assadi, Hayder M. A. Ali

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Algorithms of Classification of Mass Problems of Production Subject Domains by Malakhov, Eugene, Shchelkonogov, Denys, Mezhuyev, Vitaliy

“…This paper develops the algorithms for classification of mass problems of production subject domains. …”
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Enhanced dynamic security assessment for power system under normal and fake tripping contingencies. by A. Salih, Qusay

“…The hybrid logistic model tree (hybrid LMT) approach proposed in this study combines the symmetrical uncertainties (SU) algorithm and the logistic model tree (LMT) algorithm. …”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

“…The recorded kappa statistic value of 0.9802, and the Receiver Operating Curve (ROC) area of 98.73 %. The Random Tree relay algorithm model presented an improved average trip decision time of 18 ms compared with the standard minimum value of 20 ms recorded for the conventional relay due to eliminated communication channels. …”
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Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin

“…The models cover part load as well as full load operating conditions. The fuzzy models are trained applying locally linear model tree algorithm followed by a meta-heuristic nature inspired algorithm called bat algorithm. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Developing an app for streamlined inventory tracking with barcode scanning and load planning optimization by Teng, Yan Xin

“…Keywords: Inventory Management, Barcode Scanning, Load Planning, Binary Tree Bin Packing Algorithm, Mobile Application Development. …”
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Predicting customer churn in telecommunication service provider industry using Random Forest / Wan Muhammad Naqib Zafran Wan Roslan by Wan Roslan, Wan Muhammad Naqib Zafran

“…Through many experimentation, it was found that a model with 20 trees, a maximum depth of 5, and a maximum of 8 features yielded the highest accuracy at 79%, with an area under the curve of 0.79 for the Receiver Operating Characteristics. …”
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Comparative study of informative acoustic features for VTOL UAV faulty prediction using machine learning by Mohd Sani, Fareisya Zulaikha, Makhtar, Siti Noormiza, Mohd Nor, Elya, Kamarudin, Nur Diyana, Md Ali, Syaril Azrad, Md Ali, Kurnianingsih

“…Medium tree, Gaussian Naive Bayes and Ensemble Subspace k Nearest Neighbour algorithms are used for classification performance comparison. …”
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Crown counting and mapping of missing oil palm tree using airborne imaging system by Kee, Ya Wern

“…The overall accuracy of counting existing oil palm trees using the approach developed in this study is 93.3% while missing trees detection gives the detection accuracy of 89.2%. …”
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Comparison of path planning in simulated robot by Ch’ng, Chee Yu’ng

“…There are 4 path planning algorithms will be compared, which are Dijkstra’s algorithm, A* algorithm, RapidExploring Random Tree (RRT) algorithm, and the last one is an algorithm modified from A*. …”
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Research on risk detection of autonomous vehicle based on rapidly-exploring random tree by Yincong Ma, Lim, Kit Guan, Tan, Min Keng, Sin, Helen Ee Chuo, Ali Farzamnia, Tze, Kenneth Kin Teo

“…Since path planning plays a key role in the operation of autonomous vehicles, scholars attach great importance to this field. …”
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Random forest algorithm for co2 water alternating gas incremental recovery factor prediction by Belazreg, L., Mahmood, S.M., Aulia, A.

“…A Random Forest prediction model that predicts the WAG incremental recovery factor as a function of the eight input vectors was developed. The optimum developed model consists of 60 decision trees with a maximum depth of seven (7). …”
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Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

“…Additionally, pre-processing is conducted using the RapidMiner application prior to mapping the cleaned data with three distinct algorithms for predictive analysis: Decision Tree, Random Forest, and Multiple Linear Regression techniques. …”
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Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…It leads to network disturbances, interruption of communication and significant damage to services. Researchers seek to develop intelligent algorithms to detect and prevent DDoS attacks. …”
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