Search Results - (( variable detection method algorithm ) OR ( using vectorization means algorithm ))

Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar A., Kanthasamy R., Sait H.H., Zwawi M., Algarni M., Ayodele B.V., Cheng C.K., Wei L.J.

Development of sorting system for oil palm in vitro shoots using machine vision approach by Al-Ruhaimi, Hamdan Yahya Ahmed

“…Ultimately, the sorting algorithm performance came to be evaluated by support vector machine algorithm. …”
Get full text
Get full text

Error concealment technique using wavelet neural network for wireless transmitted digital images by Al-Azzawi, Alaa Khamees

“…In the case, where the missing regions of pixels are containing textures, edges, and other image features that are not easily handled by concealment algorithms. It therefore, necessitated to use denoising rather than EC algorithms. …”
Get full text
Get full text

Detection and Classification of Moving Objects for an Automated Surveillance System by Md. Tomari, Mohd Razali

“…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
Get full text
Get full text

Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

“…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
Get full text
Get full text

Detection and classification of moving objects for an automated surveillance system by Md Tomari, Mohd Razali

“…The applied post processing module capable to remove noise and shadow from the detected objects with less than 1% of error. Finally, classification algorithm that makes use of the extracted moment values from the detected objects successfully categorize objects into pre-defined classes of human and vehicle with 89.08% of accuracy. …”
Get full text
Get full text

Improved robust estimator and clustering procedures for multivariate outliers detection by Sharifah Sakinah, Syed Abd Mutalib

“…One of the methods to detect outliers in multivariate data is by using distance-based methods, which is Mahalanobis distance (MD). …”
Get full text
Get full text

Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms by Afzal, Asif, Alshahrani, Saad, Alrobaian, Abdulrahman, Buradi, Abdulrajak, Khan, Sher Afghan

“…This work aims to model the combined cycle power plant (CCPP) using different algorithms. The algorithms used are Ridge, Linear regressor (LR), and support vector regressor (SVR). …”
Get full text
Get full text
Get full text
Get full text

Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
Get full text
Get full text

Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
Get full text
Get full text

Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…The lvABC algorithm is introduced to overcome the local optima problem by enriching the searching behaviour using Levy mutation. …”
Get full text
Get full text
Get full text

A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
Get full text
Get full text

Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

“…The results obtained from the simulation study and real data sets indicate that the proposed method possesses high detection power with minimal misclassification error compared to the MRCD and MDP methods. …”
Get full text
Get full text

Short term forecasting based on hybrid least squares support vector machines by Zuriani, Mustaffa, M. H., Sulaiman, Ernawan, Ferda, Noorhuzaimi, Mohd Noor

“…In this study, hybrid Least Squares Support Vector Machines (LSSVM) with four meta-heuristic algorithms viz. …”
Get full text
Get full text
Get full text

Web Algorithm search engine based network modelling of Malaria Transmission by Eze, Monday Okpoto

“…MATLAB was used to implement the model system. The output shows the public places which habour the infected malaria vectors, and their corresponding vector densities. …”
Get full text
Get full text
Get full text

Ontology-based indexing of annotated images using semantic DNA and vector space model by Engku Fadzli Hasan, Syed Abdullah, Setchi, Rossitza

“…The proposed approach is evaluated by comparing the indexing achieved using the proposed semantic algorithm with results obtained using a traditional TF-based indexing in vector space model (VSM) with singular value decomposition (SVD) technique. …”
Get full text
Get full text

Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

“…The performance of the proposed algorithms are compared with quaternion least mean square QLMS, zero-attract quaternion least mean square ZA-QLMS, and widely linear quaternion least mean square WL-QLMS algorithms. …”
Get full text
Get full text
Get full text

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”

A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

“…Five evaluation metrics were utilized; mean average percent error (MAPE), accuracy, symmetric mean absolute percent error (SMAPE), root mean square percent error (RMSPE) and fitness value. …”
Get full text
Get full text

Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
Get full text
Get full text