Search Results - optimal ((((bus algorithm) OR (((bayes algorithm) OR (_ algorithm))))) OR (tree algorithm))

Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…Consequently, during peak hours, finding a vacant parking bay is more of a difficult task. This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Optimized routing algorithm for mobile multicast source in Wireless Mesh Networks by Sanni, Mistura Laide, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Anwar, Farhat, Ahmed, Gharib Subhi Mahmoud

“…Thus this paper proposes a Differential Evolution based optimized mobile multicast routing algorithm for the shared tree architecture. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

“…However, these algorithms suffer from many lacks especially when apply to detect new type of attacks, and need for new algorithms such as JAYA algorithm, teaching learning-based optimization algorithm (TLBO) algorithm is arise. …”
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Classification of Diabetes Mellitus using Ensemble Algorithms by Noor, N.A.B.S., Elamvazuthi, I., Yahya, N.

“…The objective of this study is to perform DM classification using various machine learning algorithms. In this paper, individual classifiers such as Support Vector Machine, Naïve Bayes, Bayes Net, Decision Stump, k - Nearest Neighbors, Logistic Regression, Multilayer Perceptron and Decision Tree are experimented. …”
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A direct ensemble classifier for imbalanced multiclass learning by Sainin, Mohd Shamrie, Alfred, Rayner

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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…There exist numerous algorithms to address the need of text categorization including Naive Bayes, k-nearest-neighbor classifier, and decision trees. …”
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Characterisation of pineapple cultivars under different storage conditions using infrared thermal imaging coupled with machine learning algorithms by Mohd Ali, Maimunah, Hashim, Norhashila, Abd Aziz, Samsuzana, Lasekan, Ola

“…Several types of machine learning algorithms were compared, including linear discriminant analysis, quadratic discriminant analysis, support vector machine, k-nearest neighbour, decision tree, and naïve Bayes, to obtain the best performance for the classification of pineapple cultivars. …”
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Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm by Mohammed, Zahraa Abdulkareem

“…These two algorithms are compared to their original artificial intelligence algorithms, i.e. particle swarm optimization algorithm and genetic algorithm. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Hui, Bian, Chiew, Kang Leng

“…This study investigates the performance of various conventional machine learning algorithms, including decision trees, naive Bayes, naive Bayes trees, random forest, random trees, MLP, and SVM, in detecting network intrusions using binary and multi-classification approaches. …”
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Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

“…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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Optimality of bus-invert coding by Rokhani, Fakhrul Zaman, Kan, Wen Chih, Kieffer, John, Sobelman, Gerald E.

“…To do so, we first represent the bus and invert line using a trellis diagram. Then, we show that applying bus-invert coding to a sequence of words gives the same result as would be obtained by using the Viterbi algorithm, which is known to be optimal. …”
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Artificial bee colony algorithm for solving optimal power flow problem by Le Dinh, L., Vo Ngoc, D., Vasant, P.

“…The proposed algorithm has been tested on the IEEE 30-bus, 57-bus, and 118-bus systems. …”
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Performance evaluation of intrusion detection system using selected features and machine learning classifiers by Raja Mahmood, Raja Azlina, Abdi, AmirHossien, Hussin, Masnida

“…These evolutionary-based algorithms are known to be effective in solving optimization problems. …”
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Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems by Sulaiman, Mohd Herwan

“…In this research, new nature-inspired meta-heuristic optimization algorithms namely moth-flame optimizer (MFO) and Ant Lion Optimizer (ALO) were implemented to address the optimal reactive power dispatch (ORPD) problems. …”
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Optimal under voltage load shedding based on stability index by using artificial neural network by Sharman, Sundarajoo

“…The developed algorithm was tested on IEEE 33-Bus and IEEE 69-Bus radial distribution systems. …”
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Optimal power flow solutions for power system operations using moth-flame optimization algorithm by Salman Ameen Ali, Abdullah Alabd

“…In IEEE 57-bus test system, MFO offers a minimization of 19.16% compared to 19.03% and 18.98% for Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA) respectively. …”
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