Search Results - (( internal detection method algorithm ) OR ( parameter optimization method algorithm ))

Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…Optimization algorithms are widely used for the identification of intrusion. …”
Get full text
Get full text
Get full text

Fuzzy modelling using butterfly optimization algorithm for phishing detection by Noor Syahirah, Nordin, Mohd Arfian, Ismail, Nurul Aswa, Omar

“…To generate the fuzzy parameter automatically, an optimization method is required and Butterfly Optimization Algorithm (BOA) is one of the good methods to be applied. …”
Get full text
Get full text
Get full text
Get full text

Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Mohd Ibrahim, Shapiai

“…This study focuses on using GSA method, a new computational intelligence algorithm. …”
Get full text
Get full text
Get full text

A fast learning network with improved particle swarm optimization for intrusion detection system by Ali, Mohammed Hasan

“…However, the internal power parameters (weight and basis) of FLN are initialized at random, causing the algorithm to be unstable. …”
Get full text
Get full text

Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
Get full text
Get full text

Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks by Wang Jie, Mohd. Kamal Mohd. Shah, Choong Wai Heng, Nahiyan Al-Azad

“…To enhance the accuracy of predicting pipeline defect sizes, this study introduces a magnetic leakage detection system, employing Backpropagation (BP) neural networks optimized with genetic algorithms. Traditional BP networks face challenges, including parameter determination and slow convergence, addressed through genetic algorithms' global search capabilities. …”
Get full text
Get full text
Get full text
Get full text

Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

“…The proposed ELM prevents several backpropagation issues by reducing the used of many parameters that solves the main drawbacks of Backpropagation algorithm that uses during the training phase of Neural Network. …”
Get full text
Get full text

A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
Get full text
Get full text
Get full text

Black hole algorithm along edge detector and circular hough transform based iris projection with biometric identification systems by Tara Othman Qadir, Tara Othman Qadir, N.S.A.M Taujuddin, N.S.A.M Taujuddin

“…In this study, we presented a Black Hole Algorithm (BHA) along the Canny edge detector and circular Hough transform-based optimization technique for circular parameter identification of iris segmentation. …”
Get full text
Get full text

Optimization of feature selection in Support Vector Machines (SVM) using recursive feature elimination (RFE) and particle swarm optimization (PSO) for heart disease detection by Bayuaji, Luhur, Kusnadi, Kusnadi, Amzah, Mochamad Yamin, Pebrianti, Dwi

“…RFE combines a dimensionality reduction process with a machine learning process where the least important features are iteratively removed until the best feature subset is obtained, while the PSO method is used to optimize the C and gamma parameters of SVM. …”
Get full text
Get full text
Get full text
Get full text

Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…On the other hand, when we use computers to reduce uncertainty, the computer itself can become an expert in a specific field through a variety of methods. One such method is machine learning, which involves computer algorithm to capture hidden knowledge from data. …”
Get full text
Get full text

A novel islanding detection technique using modified Slantlet transform in multi-distributed generation by Hizam, Hashim, Ahmadipour, Masoud, Mohd Radzi, Mohd Amran, Othman, Mohammad Lutfi, Chireh, Nikta

“…In this paper, a new hybrid islanding detection scheme based on a combination of a modified Slantlet Transform (MSLT) and machine learning is applied to a passive time frequency islanding detection of multiple distributed generation units. A Harmony Search Algorithm (HSA) is used to optimally specify suitable scales of Slantlet transform and Slantlet decomposition levels for accurate islanding classification. …”
Get full text
Get full text
Get full text

Impact of low-dose protocols on computed tomography of lung cancer screening on the intrinsic performance metrics: a phantom study by Karim, M.K.A., Khalidi, M. E., Chew, M. T., Kechik, M. M. A., Mazlan, D., Ng, K. H.

“…Introduction: This research aims to assess the task-based performance of low dose CT lung examination with different acquisition parameters, evaluate the acquisition parameters of lung cancer in low dose CT lung examination, and explore the effect of the iterative reconstruction (IR) algorithm on the image quality of low dose CT for CT lung examination. …”
Get full text
Get full text

Application Studies, Part-I: Model Identification and Validation by Lemma, T.A.

“…In Chaps. 4 and 5, all the theories needed for developing fault detection relevant models in either static or dynamic conditions, and a method for estimating their uncertainties, respectively, have been thoroughly discussed. …”
Get full text
Get full text

Application Studies, Part-I: Model Identification and Validation by Lemma, T.A.

“…In Chaps. 4 and 5, all the theories needed for developing fault detection relevant models in either static or dynamic conditions, and a method for estimating their uncertainties, respectively, have been thoroughly discussed. …”
Get full text
Get full text

Facial geometry and speech analysis for depression detection by Pampouchidou, A., Simantiraki, O., Vazakopoulou, C.-M., Chatzaki, C., Pediaditis, M., Maridaki, A., Marias, K., Simos, P., Yang, F., Meriaudeau, F., Tsiknakis, M.

“…The proposed system has been tested both in gender independent and gender based modes, and with different fusion methods. The algorithms were evaluated for several combinations of parameters and classification schemes, on the dataset provided by the Audio/Visual Emotion Challenge of 2013 and 2014. …”
Get full text
Get full text

Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

“…Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. …”
Get full text
Get full text

Implementation of YOLOv8-seg on store products to speed up the scanning process at point of sales by Hanna Arini, Parhusip, Suryasatriya, Trihandaru, Denny, Indrajaya, Jane, Labadin

“…The novelty lies in the customization and optimization of YOLOv8-seg for detecting and segmenting 30 specific Indonesian products. …”
Get full text
Get full text
Get full text
Get full text

Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
Get full text
Get full text

Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
Get full text
Get full text
Get full text