Search Results - (( based optimization method algorithm ) OR ( using vectorization means algorithm ))

Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
Get full text
Get full text
Get full text
Get full text

A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom, Sampe, Jahariah

“…In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
Get full text
Get full text

Logistic regression methods for classification of imbalanced data sets by Santi Puteri Rahayu, -

“…These results can be seen as further explanation on the success of Truncated Newton method in TR-KLR and TR Iteratively Re-weighted Least Square (TR-IRLS) algorithm respectively, because of the equivalence of iterative method used by these algorithms. …”
Get full text
Get full text

A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection by Selamat, Nur Asmiza, Md. Ali, Sawal Hamid, Minhad, Khairun Nisa’, Ahmad, Siti Anom

“…In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
Get full text
Get full text
Get full text

An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum by Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
Get full text
Get full text
Get full text

Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
Get full text
Get full text

A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
Get full text
Get full text
Get full text
Get full text

A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

“…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
Get full text
Get full text
Get full text
Get full text

Optimal short term load forecasting using LSSVM and improved BFOA considering Malaysia pandemic disrupted situation by Zaini, Farah Anishah

“…Due to that reason, in this study, the hybrid forecasting model based on the Least Square Support Vector Machine (LSSVM) and Improved Bacterial Foraging Optimization Algorithm (IBFOA) is developed to perform an accurate STLF and applied to load in Peninsular Malaysia during the pandemic disrupted situation. …”
Get full text
Get full text
Get full text
Get full text

Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
Get full text
Get full text

Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

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

Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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

“…The hierarchical fuzzy clustering method developed here is far better than a similar implementation of the hard k-means method. …”
Get full text
Get full text

Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework by Aidil Zulkafli, Nadhirah, Elyca Anak Bundak, Caceja, Amiruddin Abd Rahman, Mohd, Chin Yap, Chi, Chong, Kok-Keong, Tee Tan, Sin

“…This novel study demonstrated that support vector regression (SVR) integrated with the particle swarm optimization (PSO) model is an alternative method to predict the device performance in future organic solar cells.…”
Get full text
Get full text
Get full text

A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
Get full text
Get full text

State of charge estimation of lithium-ion batteries in an electric vehicle using hybrid metaheuristic - deep neural networks models by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Isuwa, Jeremiah

“…The proposed TLBO-deep neural networks (TLBO-DNNs) method was evaluated on a dataset of 1,064,000 samples, with performance assessed using mean absolute error (MAE), root mean square error (RMSE), and convergence value. …”
Get full text
Get full text
Get full text

Tailoring the energy harvesting capacity of zinc selenide semiconductor nanomaterial through optical band gap modeling using genetically optimized intelligent method by Olubosede, Olusayo, Abd Rahman, Mohd Amiruddin, Alqahtani, Abdullah, Souiyah, Miloud, Latif, Mouftahou B., Oke, Wasiu Adeyemi, Aldhafferi, Nahier, Owolabi, Taoreed O.

“…This present work provides novel ways whereby the wide energy band gap of zinc selenide can be effectively modulated and tuned for light energy harvesting capacity enhancement by hybridizing a support vector regression algorithm (SVR) with a genetic algorithm (GA) for parameter combinatory optimization. …”
Get full text
Get full text

Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

“…Supervised and unsupervised machine learning algorithms particularly the Support Vector Machine (SVM) and Density Based Spatial Clustering of Application with Noise (DBSCAN) are used in this study. …”
Get full text
Get full text
Get full text

Comparative Assessment of Improved SVM Method under Different Kernel Functions for Predicting Multi-scale Drought Index by Pande C.B., Kushwaha N.L., Orimoloye I.R., Kumar R., Abdo H.G., Tolche A.D., Elbeltagi A.