Search Results - (( using function means algorithm ) OR ( pattern classification issues algorithm ))

Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

“…Subsequently,the filtered signal containing useful information was extracted by three methods  root mean square (RMS),mean absolute value (MAV),and autoregressive (AR) covariance,all of which are commonly used in TD.A comparative analysis of the three different techniques was performed based on the accuracy performance of the EMG pattern classification using linear vector quantization (LVQ) neural network.In the experimental work undertaken,six healthy subjects comprised of males and females were selected. …”
Get full text
Get full text
Get full text
Get full text

A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
Get full text
Get full text

Development of drift conversion algorithm for ISFET based pH sensor for continuous measurement system by Othman, Md Rizal, Najib, Muhammad Sharfi, Muda, Razali, Sulaiman, Mohd Herwan, Noordin, Nurul Hazlina, Hadi, Amran Abdul, Kamaludin, Mohamad Yusof, Mohd Ismahad, Syono

Get full text
Get full text

Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

“…The use of UV/Vis, IR, and Raman spectroscopy for disease classification is also highlighted. To conclude, many pattern recognition algorithms have the potential to overcome each of their distinct limits, and there is also the option of combining all of these algorithms to create an ensemble of methods.…”
Get full text
Get full text
Get full text
Get full text
Get full text

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

Get full text
Get full text

Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

“…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
Get full text
Get full text
Get full text

Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

Get full text
Get full text
Get full text

Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

“…Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues. …”
Get full text
Get full text
Get full text

Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

“…Pattern classification is one of the major components for the design and development of a computerized pattern recognition system. …”
Get full text
Get full text

Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan C.H., Tan M.S., Chang S.-W., Yap K.S., Yap H.J., Wong S.Y.

Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

Get full text
Get full text
Get full text

Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

“…However, the MBGWO has several issues in finding a good quality solution. Thus, this study proposes an enhanced binary grey wolf optimiser (EBGWO) algorithm for FS in anomaly detection to overcome the algorithm issues. …”
Get full text
Get full text

Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System by R.Badlishah, Ahmad, Nawir, M., Amir, A, Yaakob, N, Mat Safar, A, Mohd Warip, M.N, Zunaidi, I

“…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
Get full text
Get full text

Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System by Badlishah, Ahmad, Nawir, M., Amir, A, Yaakob, N, Mat Safar, A, Mohd Warip, M.N, Zunaidi, I

“…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
Get full text
Get full text

Hybrid Models Of Fuzzy Artmap And Qlearning For Pattern Classification by Navan, Farhad Pourpanah

“…. ________________________________________________________________________________________________________________________ Pattern classification is one of the primary issues in various data mining tasks. …”
Get full text
Get full text

Rough Set Discretize Classification of Intrusion Detection System by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Many pattern classification tasks confront with the problem that may have a very high dimensional feature space like in Intrusion Detection System (IDS) data. …”
Get full text
Get full text
Get full text

Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

“…The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. …”
Get full text
Get full text

Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

“…The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. …”
Get full text
Get full text

Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

“…It is attained successfully by combining the mean in K-Means algorithm, minimum and maximum in K-Midranges algorithm and compute their average as mean cluster of Hybrid mean. …”
Get full text
Get full text
Get full text

Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

“…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
Get full text
Get full text