Search Results - (( using function means algorithm ) OR ( parameter classifications using algorithm ))

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
Get full text
Get full text

Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
Get full text
Get full text

An improvement of back propagation algorithm using halley third order optimisation method for classification problems by Abdul Hamid, Norhamreeza

Get full text
Get full text
Get full text
Get full text

RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm by Basri, S.M.M., Nawi, N.M., Mamat, M., Hamid, N.A.

“…This paper introduced a new class of efficient second order conjugate gradient (CG) for training BP called Rivaie, Mustafa, Ismail and Leong (RMIL)/AG. The RMIL uses the value of adaptive gain parameter in the activation function to modify the gradient based search direction. …”
Get full text
Get full text
Get full text

Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar by Anuar, Norhasnelly

“…The objectives of this project are to use FCM as the clustering algorithm to establish TLPs. …”
Get full text
Get full text

Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm by Rehman Gillani, Syed Muhammad Zubair

“…The traditional Back-propagation Neural Network (BPNN) is a supervised Artificial Neural Networks (ANN) algorithm. It is widely used in solving many real time problems in world. …”
Get full text
Get full text
Get full text
Get full text

Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

“…Previously, there is limited work on the clustering and classification of biologically active compounds into their activity based classes using fuzzy and neural network. …”
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 gender and race recognition system using speech and recognition by using frequency spectrum by Ng Siew Fong

“…In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. …”
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

Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.] by Rahiman, Mohd Hezri Fazalul, Ismail, Nurlaila, Taib, Mohd Nasir, Mohd Ali, Nor Azah, Tajuddin, Saiful Nizam

“…Back-propagation training algorithm and sigmoid transfer function were used to optimise the parameters in the training network. …”
Get full text
Get full text
Get full text

Generating type 2 trapezoidal fuzzy membership function using genetic tuning by Khairuddin, S.H., Hasan, M.H., Akhir, E.A.P., Hashmani, M.A.

“…This paper focuses on the construction of interval type 2 (IT2) trapezoidal shape MF from fuzzy C Means (FCM) that is used for fuzzification process of mamdani FIS. …”
Get full text
Get full text

Generating type 2 trapezoidal fuzzy membership function using genetic tuning by Khairuddin, S.H., Hasan, M.H., Akhir, E.A.P., Hashmani, M.A.

“…This paper focuses on the construction of interval type 2 (IT2) trapezoidal shape MF from fuzzy C Means (FCM) that is used for fuzzification process of mamdani FIS. …”
Get full text
Get full text

Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
Get full text
Get full text
Get full text

Local gray level S-curve transformation – A generalized contrast enhancement technique for medical images by Gandhamal, A., Talbar, S., Gajre, S., Hani, A.F.M., Kumar, D.

“…The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. © 2017 Elsevier Ltd…”
Get full text
Get full text

Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. …”
Get full text
Get full text
Get full text

Detection of sweetness level for fruits (watermelon) with machine learning by Wan Nazulan, Wan Nurul Suraya, Asnawi, Ani Liza, Mohd Ramli, Huda Adibah, Jusoh, Ahmad Zamani, Ibrahim, Siti Noorjannah, Mohamed Azmin, Nor Fadhillah

“…The objective of this work is to investigate the sweetness parameter for the fruit’s detection and classification algorithm in machine learnings. …”
Get full text
Get full text
Get full text
Get full text

Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
Get full text
Get full text
Get full text

Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
Get full text
Get full text

Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
Get full text
Get full text
Get full text