Search Results - data extraction ((bees algorithm) OR (based algorithm))

Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network by Muhammad Sidik, Siti Syatirah

“…This proposed model will be employed in the Improved Reverse Analysis method to extract the relationship between various fields of real-life data sets based on logical representation. …”
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Objects tracking from natural features in mobile augmented reality by Ng, Edmund Giap Weng, Rehman, Ullah Khan, Shahren, Ahmad Zaidi Adruce, Oon, Yin Bee

“…The pose matrix from extracted features was calculated by Homography. The adapted algorithm was tested in a mobile AR-prototype application using iPhone. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…In this paper, the filter method chi square and the Artificial Bee Colony) ABC algorithm were both used as FS methods . …”
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Artificial Bee Colony With Differential Evolution Algorithm For Feature Extraction And Selection Of Mass Spectrometry Data by Mohamed Yusoff, Syarifah Adilah

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IMPLEMENTATION OF A TIME SERIES PREDICTION ALGORITHM FOR COVID-19 CONFIRMED CASES IN MALAYSIA : A PRELIMANARY STUDY AFTER THE RECOVERY MOVEMENT CONTROL ORDER by Tee, Bee Lin

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An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types by Selamat, Harihodin, Mohd. Rahim, Mohd. Shafry, Daman, Daut

“…The sequential recognition algorithm is to solve the time consuming issues for extracting sequential data. …”
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Individual-tree segmentation and extraction based on LiDAR point cloud data by Liu, Xiaofeng, Abdullah, Muhamad Taufik, Mustaffa, Mas Rina, Nasharuddin, Nurul Amelina

“…In the task of individual tree extraction, the point cloud distance discriminant clustering algorithm outperformed the watershed algorithm. …”
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Pengekstrakan data berasaskan pendekatan ontologi: kes data jujukan hidrologi by Abd. Hamid, Ahmad Ghadaffi

“…The sequential recognition algorithm is to solve the time consuming issues for extracting sequential data. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

“…Recently, several effective supervised and unsupervised machine learning methods have been developed in the domain of topics extraction. However, less works have been conducted in applying multiobjective based algorithm for topic extraction. …”
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A buffer-based online clustering for evolving data stream by Islam, Md. Kamrul, Ahmed, Md. Manjur, Kamal Z., Zamli

“…In this study, we present a fully online density-based clustering algorithm called buffer-based online clustering for evolving data stream (BOCEDS). …”
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Fatigue data editing algorithm for automotive applications by Shahrum Abdullah, John R. Yates, Joseph A. Giacornin

“…This paper presents a wavelet based algorithm to summa rise a long record of fatigue signal by extracting the bumps (fatigue damaging events) to produce a bump signal. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning by Islam, Md Kamrul

“…Data stream clustering plays an important role in data stream mining for knowledge extraction. …”
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HAPTIC VISUALIZATION USING VISUAL TEXTURE INFORMATION by Adi, Waskito

“…Wavelet decomposition is utilized to extract data information from texture data. In searching process, the data are retrieved based on data distribution. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…A critical step in developing such intelligent systems is the feature extraction process. Feature extraction is essential in classification, especially for data sources in the form of images. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

“…Recently, several effective supervised and unsupervised machine learning methods have been developed in the domain of topics extraction. However, less works have been conducted in applying multiobjective based algorithm for topic extraction. …”
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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title by Khalaf, Emad Taha

“…The enhanced method combines three transformation methods for analyzing the iris image and extracting its local features. It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion by Zafar, R., Dass, S.C., Malik, A.S.

“…In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. …”
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Agent-based extraction algorithm for computational problem solving by Rajabi, Maryam

“…The results show that the extraction algorithm has been able to extract 100 % of the information correctly. …”
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