Search Results - (( developing separation selection algorithm ) OR ( java implication based algorithm ))

Genetic algorithm based ensemble framework for sentiment analysis by Lai, Po Hung

“…Prior to developing the whole multilayered ensemble framework, two separate experiments were performed to evaluate and study the different methods of feature extraction and selection. …”
Get full text
Get full text

A Comprehensive Study on CO2-CH4 Gas Separation Using γ-Alumina Membrane and Parameters Affecting Permeability and Separation Behavior by AHMAD, FATIN MUNIRAH

“…The methodology is divided into two algorithms for permeability and separation perfomance respectively. …”
Get full text
Get full text

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

Get full text
Get full text
Get full text

Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction by Nasser, Abdullah, H.M. Ghanem, Waheed Ali, H.Y. Saad, Abdul-Malik, Hamed Abdul-Qawy, Antar Shaddad, A. Ghaleb, Sanaa A, Mohammed Alduais, Nayef Abdulwahab, Din, Fakhrud, Ghetas, Mohamed

“…To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
Get full text
Get full text
Get full text

Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image by Samsudin, Sarah Hanim

“…Three feature selection algorithms of Genetic Algorithm (GA), Support Vector Machine (SVM) and Random Forest (RF) were used to select the most significant wavelengths since the algorithms works well with large size of data and widely applied for feature selection of hyperspectral remote sensing data. …”
Get full text
Get full text

A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. …”
Get full text
Get full text
Get full text

DESIGN AND DEVELOPMENT OF HIGH-ACCURACY MACHINE FOR WIRE BENDING by Mustafa F.F., Hussein O., Fakhri O.F., Sabri A.H.

“…The main point depends on the proposed algorithm, which has been developed based on separating the process, in which the central controller is responsible mainly for controlling the sub-controller, where the sub-controllers are programmed using PID to control the entire mechanisms of feeding and bending separately and ensure that the outcomes of these mechanisms are compatible with the input data from the central controller. …”

An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
Get full text
Get full text

Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field by Toh, Cheng Chuan

“…Blind Source Separation (BSS) refers to the statistical technique of separating a mixture of underlying source signals.BSS denotes as a phenomena and separation on mixed heart-lung sound is one of its example.The challenge of this research is to separate the separate lung sound and heart sound from mixed heart-lung sound.A clear lung sound for diagnosis purpose able to be obtained after separating the mixed heart-lung sound.In biomedical field,lung information is precious due to it has been provided for respiratory diagnosis.However,the interference of heart sound towards lung sound will generate ambiguity and it will lead to drop down the accuracy of diagnosis.Thus,a clean lung sound is needed to increases the accuracy of diagnosis.One of the ways for non-invasive respiratory diagnosis for obtaining lung information is through extracting lung sound from mixed heart-lung sound by using Two-Dimensional Nonnegative Matrix Factorization (NMF2D) algorithm.This method is based on cocktail party effect in which it refers to human brain able to selectively listen to target among a cacophony of conversations and background noise and this considered as a difficult task to machine.Therefore, duplication on cocktail party effect into machine is used to separate the mixed heart-lung sound.This research presents a novel approach NMF2D algorithm in which a suitable model for signal mixture that accommodated the reverberations and nonlinearity of the signals.The objectives of this research are focusing on investigating the useful signal analysis algorithms,defining a new technique of signal separability,designing and developing novel methods for BSS. …”
Get full text
Get full text
Get full text
Get full text

Fast shot boundary detection based on separable moments and support vector machine by Idan, Zinah N., Abdulhussain, Sadiq H., Mahmmod, Basheera M., Al-Utaibi, Khaled A., Syed Abdul Rahman Al-, Syed Abdul Rahman Al-Hadad, Sait, Sadiq M.

“…The proposed SBD framework is based on the concept of candidate segment selection with frame active area and separable moments. …”
Get full text
Get full text
Get full text

Using fuzzy association rule mining in cancer classification by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

“…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
Get full text
Get full text

Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method by Al-Mohair, Hani Kaid Saif

“…The Differential Evolution Algorithm (DE) is used in this work to select the optimum color and texture information to achieve the optimum response. …”
Get full text
Get full text

Application of fuzzy clustering analysis to compound datasets for drug lead identification by Sinarwati, Mohamad Suhaili, Mohamad Nazim, Jambli, Abdul Rahman, Mat

“…However, there are little study on overlapping method such as fuzzy cmean (FCM) and fuzzy c-varieties (FCV) clustering algorithms. Therefore, these two clustering algorithms are applied and their performance is compared based on the effectiveness of the clustering results in terms of separation between actives and inactives (Pa) into different clusters and mean intercluster molecular dissimilarity (MIMDS). …”
Get full text
Get full text
Get full text

Generalization of Map Details within Computer Assisted Cartography by Yusuf, Matharuddin

“…subjectivity in generalization, the metamorphasis from manual to digital techniques in cartography has resulted in the development of computer algorithms designed to replicate many tasks previously performed by humans. …”
Get full text
Get full text

Identification and Grading of Manage Using Image Processing by Shukor, Syazwan

“…Features such as maximum colour component values, pixel area and perimeter are extracted using a feature extraction algorithm for compilation into separate "sv" files for classifier and prediction models training and testing. 3 classes are selected using silhouette analysis in labelling the mango features as training references for classifiers. …”
Get full text
Get full text

Spectral feature selection and classification of roofing materials using field spectroscopy data by Samsudin, Sarah Hanim, M. Shafri, Helmi Z., Hamedianfar, Alireza, Mansor, Shattri

“…Therefore, this research used feature selection algorithms of the support vector machine (SVM), genetic algorithm (GA), and random forest (RF) to select the most significant wavelengths, and the separability between classes was assessed using the SVM classification. …”
Get full text
Get full text
Get full text

Computer-aided acute leukemia blast cells segmentation in peripheral blood images by Madhloom, H.T., Kareem, S.A., Ariffin, H.

“…The method also introduces an approach to split overlapping cells using the marker-controlled watershed algorithm based on a new marker selection scheme. Furthermore, the paper presents a powerful approach to separate the nucleus region and the cytoplasm region based on the seeded region growing algorithm powered by histogram equalization and arithmetic addition to handle the issue of non-homogenous nuclear chromatin pattern. …”
Get full text

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Artificial neural network (ANN) as post-processing stage for chemically selective field effect transistor (CHEMFET) sensor selectivity based-on ion concentration / Nurhakimah Abd A... by Abd Aziz, Nurhakimah

“…This is confirmed based on statistical analysis validation via regression analysis that shows with R-factor of 0.9011. Other than developing supervised learning, this study also was focusing on exploration of unsupervised learning mainly in blind source separation (BSS) algorithm to separate the interface signal. …”
Get full text
Get full text

Development Of Hierarchical Skin-Adaboost-Neural Network (H-Skann) For Multiface Detection In Video Surveillance System by Zakaria, Zulhadi

Get full text
Get full text