Search Results - model ((((replication algorithm) OR (selection algorithm))) OR (detection algorithm))

A novel deadlock detection algorithm for neighbour replication on grid environment by Noriyani, Mohd Zin

“…The NRGDD is compared with Multi-Cycle of Deadlock Detection and Recovery (MC2DR) algorithm based on the time required for both models to detect two deadlock cycles and using different numbers of transactions. …”
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A sequential handwriting recognition model based on a dynamically configurable convolution recurrent neural network and hybrid salp swarm algorithm by Ahmed Ali Mohammed, Al-saffar

“…The built DCCRNN is based on the Salp Swarm optimization Algorithm (SSA), a processor that given a particular dataset will find the best CRNN’s structure and hyperparameters. …”
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Data-driven multi-fault detection in pipelines utilizing frequency response function and artificial neural networks by Hussein, Hussein A. M, Abdul Rahim, Sharafiz, Mustapha, Faizal B., Krishnan, Prajindra S., Abdul Jalil, Nawal Aswan

“…The data underwent preprocessing, including the application of principal component analysis (PCA) for feature selection. The subsequent data processing stage involved the application of an ANN algorithm for pattern recognition to analyze and classify the acquired data, identifying patterns associated with the replicated fault conditions. …”
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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Feature selection algorithms for Malaysian dengue outbreak detection model by Husam I.S. Abuhamad, Azuraliza Abu Bakar, Suhaila Zainudin, Mazura Sahani, Zainudin Mohd Ali

“…Based on the selected features, three predictive modeling techniques (J48, DTNB and Naive Bayes) were applied for dengue outbreak detection. …”
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Replica Creation Algorithm for Data Grids by Madi, Mohammed Kamel

“…Current algorithms focus on number of accesses in deciding which file to replicate and where to place them, which ignores resources’ capabilities. …”
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Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

“…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

“…This research presents a two-phase phishing detection system by employing unsupervised feature selection and supervised classification. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

“…Negative selection algorithm has been successfully used in several purposes such as in fault detection, data integrity protection, virus detection and etc.due to the unique ability in self-recognition by classifying self or non-self’s detectors. …”
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Automated feature selection using boruta algorithm to detect mobile malware by Che Akmal, Che Yahaya, Ahmad Firdaus, Zainal Abidin, Salwana, Mohamad, Ernawan, Ferda, Mohd Faizal, Ab Razak

“…This research proposed automated feature selection using Boruta algorithm to detect the malware. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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Neural network algorithm-based fall detection modelling by Mohd Yusoff, Ainul Husna, Koh, Cheng Zhi, Ngadimon, Khairulnizam, Md Salleh, Salihatun

“…However, the improvement of model accuracy is still needed. This article presents results of modelling for fall detection system by using nonlinear autoregression neural network NARnet algorithm. …”
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Outbreak detection model based on danger theory by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak

“…Two outbreak diseases, dengue and SARS, are subjected to a danger theory algorithm; namely the dendritic cell algorithm.To evaluate the model, four measurement metrics are applied: detection rate, specificity, false alarm rate, and accuracy. …”
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An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons by Ghanem, Waheed Ali H. M., Aman, Jantan, Ahmed Ghaleb, Sanaa Abduljabbar, Naseer, Abdullah B.

“…However, the problem of improving the accuracy and efficiency of classification models remains open and yet to be resolved. This study proposes a new binary classification model for intrusion detection, based on hybridization of Artificial Bee Colony algorithm (ABC) and Dragonfly algorithm (DA) for training an artificial neural network (ANN) in order to increase the classification accuracy rate for malicious and non-malicious traffic in networks. …”
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Human face detection using skin color segmentation and watershed algorithm by Fatma Susilawati, Mohamad, Abdulganiyu, Abdu Yusuf, Zahraddeen, Sufyanu

“…The process involves transforming the face images from RGB to the selected color models; then segmentation is carried out by selecting a threshold value for each of the color models. …”
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Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms by Masrom, S., Rahman, R.A., Mohamad, M., Rahman, A.S.A., Baharun, N.

“…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms by Masrom, S., Rahman, R.A., Mohamad, M., Rahman, A.S.A., Baharun, N.

“…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

“…To achieve this, we measured the performance of three deep learning algorithms for normal and abnormal detection of IDS, and a comparison was made to select the best performance of the deep learning algorithm for detection in IDS, such as RNN, DBN and CNN. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

“…The transductive conformal prediction and outlier detection have been employed for feature selection algorithm. …”
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