Search Results - (( development program bayes algorithm ) OR ( java optimization path algorithm ))
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing
Published 2019“…This work uses iterative smoothing algorithm to find an alternative path with less distance and energy consumption. …”
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Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri
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Energy efficient path reconstruction in wireless sensor network using iPath
Published 2019“…This work uses iterative boosting algorithm to find an alternative path with less distance and energy consumption. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Visdom: Smart guide robot for visually impaired people
Published 2025“…Core functionalities such as path planning, autonomous movement, voice feedback, and app-to-robot communication have been thoroughly tested and optimized. …”
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Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu
Published 2014“…Multilayer Perceptron algorithm has been the best algorithm with the highest success percentage in both of the programs; Decision Trees has been the algorithm which has the lowest success percentage again in both of the programs. …”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir
Published 2019“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms
Published 2022“…ML can examine millions of data sets in a short period of time without being explicitly programmed to improve the results. This type of algorithm can aid financial institutions in making grant selections for their clients. …”
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Banana recognition system using convolutional neural network / Mohamad Shafiq Rosli
Published 2021“…The programming is a subject that are used by developer to provide the system. …”
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Android malware detection using permission based static analysis
Published 2024“…The increase of mobile device enhancement grows. With this development, mobile phones are supporting many programs, and everyone takes advantage of them. …”
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Android malware detection using permission based static analysis
Published 2023“…The increase of mobile device enhancement grows. With this development, mobile phones are supporting many programs, and everyone takes advantage of them. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining
Published 2023“…Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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Empirical study on intelligent android malware detection based on supervised machine learning
Published 2020“…More significantly, this paper empirically discusses and compares the performances of six supervised machine learning algorithms, known as K-Nearest Neighbors (K-NN), Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), Naïve Bayes (NB), and Logistic Regression (LR), which are commonly used in the literature for detecting malware apps.…”
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