Search Results - (( code classification learning algorithm ) OR ( simulation optimization clustering algorithm ))

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. …”
Get full text
Get full text
Get full text

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). …”
Get full text
Get full text
Get full text
Get full text

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

“…However, supervised learning technique has limitations for malware classification task. …”
Get full text
Get full text
Get full text

Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing. by Abubaker, Ahmad Asad

Get full text
Get full text

Cluster optimization in VANET using MFO algorithm and K-Means clustering by Ramlee, Sham Rizal, Hasan, Sazlinah, K. Subramaniam, Shamala

“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
Get full text
Get full text

An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

“…We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. …”
Get full text
Get full text
Get full text

Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

“…The data was gathered using real-time packet capturing tools which were then processed and moved with model development using different deep learning algorithms such as, LSTM, MLP, RNN and Autoencoders. …”
Get full text
Get full text
Get full text

Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
Get full text
Get full text
Get full text
Get full text

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.

“…Aerial photography; Aircraft detection; Antennas; Codes (symbols); Discrete cosine transforms; Discrete wavelet transforms; Glossaries; Image classification; Image coding; Image enhancement; Learning algorithms; Learning systems; Object recognition; Remote sensing; Satellite imagery; Satellites; Unmanned aerial vehicles (UAV); Discrete tchebichef transforms; Discriminative features; Finite Ridgelet Transform; Histogram of oriented gradients; Image processing and computer vision; Scale invariant feature transforms; SIFT; Sparse coding; Classification (of information)…”

Genetic algorithm optimized receiver-oriented packet clustering in multi-buffer network card by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

“…This packet clustering optimization is an expansion of our previous base network card optimization in cloud network environment, using genetic algorithm. …”
Get full text
Get full text

An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control by Adekiigbe, Adebanjo, Ahmed, Abdulghani Ali, Sadiq, Ali Safa, Ghafoor, Kayhan Zrar, Kamalrulnizam, Abu Bakar

“…The simulation results show that FLCCA performs better than Distributed Fuzzy Score based Clustering Algorithm (DFSCA).…”
Get full text
Get full text
Get full text

Improved particle swarm optimization by fast annealing algorithm by Bashath, Samar, Ismail, Amelia Ritahani

“…We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.…”
Get full text
Get full text
Get full text
Get full text

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

“…Furthermore,it is also learned that the use of structural information in the weighting scheme contribute to a better classification.…”
Get full text
Get full text
Get full text

An improved energy-efficient clustering protocol to prolong the wireless sensor network lifetime by Alhmood, Ali Abdul-Hussian Hassan

“…The simulation results prove that the IEECP prolongs the network lifetime better than Energy efficient clustering protocol based on K-means (EECPK-means)-midpoint algorithm (EECPK-means), Traffic-Aware Channel Access Algorithm (TACAA), and an optimal clustering mechanism based on Fuzzy C-means (OCM–FCM) protocols based on the First node die and Weighted first node die. …”
Get full text
Get full text
Get full text
Get full text

Cauchy density-based algorithm for VANETs clustering in 3D road environments by Jubair, Mohammed Ahmed, Ahmad, Mohd Riduan, Abdul Aziz, Izzatdin, Al-Obaidi, Ahmed Salih, Al-Tickriti, Abdullah Talaat, Hassan, Mustafa Hamid, Mostafa, Salama A., Mahdin, Hairulnizam

“…Clustering algorithms for VANETs operate in a decentralized mode, which requires incorporating additional stages before deciding the clustering decisions and might create sub-optimality due to the local nature of the decentralized approach. …”
Get full text
Get full text
Get full text

Application of kohonen neural network and rough approximation for overlapping clusters optimization by Mohebi, E., Md. Sap, Mohd. Noor

“…Experiments show that the proposed two-level algorithm is more accurate and generates fewer errors as compared with crisp clustering operations.…”
Get full text
Get full text

Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
Get full text
Get full text
Get full text

A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

“…One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. …”
Get full text
Get full text

A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

“…One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. …”
Get full text
Get full text

A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

“…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
Get full text
Get full text