Search Results - (( code classification based algorithm ) OR ( simulation optimization means algorithm ))

Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…In this method, permission-based features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

“…Several machine learning techniques based on supervised learning have been adopted in the classification of malware. …”
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Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

“…Most of the algorithms got promising results and classify packets based on DSCP accurately. …”
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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

Source code classification using latent semantic indexing with structural and frequency term weighting by Yusof, Yuhanis, Alhersh, Taha, Mahmuddin, Massudi, Mohamed Din, Aniza

“…This research proposes a Latent Semantic Indexing classifier that integrates information structural and frequency of terms in its weighting scheme.The content terms are identified by extracting words in the source code program. Based on the undertaken experiment the LSI classifier is noted to generate a higher precision and recall compared to the C4.5 algorithm. …”
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Scene classification for aerial images based on CNN using sparse coding technique by Qayyum, A., Malik, A.S., Saad, N.M., Iqbal, M., Faris Abdullah, M., Rasheed, W., Rashid Abdullah, T.A., Bin Jafaar, M.Y.

“…Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. …”
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Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

“…In video coding, research is focused on the development of fast motion estimation (ME) algorithms while keeping the coding distortion as small as possible. …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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Determining optimal location of static VAR compensator by means of genetic algorithm by Karami, Mahdi, Mariun, Norman, Ab Kadir, Mohd Zainal Abidin

“…This method is employed to optimize the stability of power system by means of maximizing distance to collapse point. …”
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Scene classification for aerial images based on CNN using sparse coding technique by Qayyum A., Malik A.S., Saad N.M., Iqbal M., Faris Abdullah M., Rasheed W., Rashid Abdullah T.A., Bin Jafaar M.Y.

Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms by Abubakar, A., Khan, A., Nawi, N.M., Rehman, M.Z., Teh, Y.W., Chiroma, H., Herawan, T.

“…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links by Arif, M., Khan, S.S., Qadri, S.S.U., Naseem, I., Moinuddin, M.

“…The analytical results are validated through simulation. Finally, extensive simulations have been done to evaluate the performance of the proposed algorithm for various choices of optimal q-values. …”
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Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean by Lorpunmanee, Siriluck, Abdullah, Abdul Razak

“…Simulation runs demonstrate that our algorithm leads to better results than the traditional algorithms for scheduling policies used in Grid environment.…”
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Modified K-Nearest Neighborhood Algorithm For Optimal Selection Of Distribution Centre In The Disaster Relief Operation by Siti Nabilah Basarang

Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms by Abubakar, Adamu, Khan, Abdullah, Nawi, Nazri Mohd, Rehman, M. Z., Teh , Ying Wah, Chiroma , Haruna, Herawan, Tutut

“…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

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Software Classification Using Structure-Based Descriptors by Ramadan, Qusai Hussein

“…A total of 2800 programs have been used during the training process while two different datasets of size (28) were used for testing. Based on the undertaken experiment, the IBK algorithm is noted to generate the highest classification accuracy (74.8%) compared to several other algorithms provided in the Weka tool. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios by Almubaidin M.A.A., Ahmed A.N., Malek M.A., Mahmoud M.A., Sherif M., El-Shafie A.

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