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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address the noise problem in multi-view data, this study enhances the gbs method and develops a new self-weighted graph multi-view clustering algorithm (swmcan). …”
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Thesis -
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Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman
Published 2015“…The main aim of this study is to develop a novel technique for suppression of metal artifacts and this study generally consists three main parts. …”
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An Improved Water-Filling Algorithm Based On Power Allocation In Network Mimo
Published 2020“…Moreover, this study focuses on the design and development of a novel power allocation algorithm, which is an extension to the previous Improved Water-Filling algorithm (IWF), namely, Low-Complexity Improved Water-Filling algorithm (LC-IWF). …”
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Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam
Published 2018“…Moreover, achieved results indicated that the developed ELM models can be used with confidence for further work on formulating novel model predictive strategy in shear strength and ductility of steel concrete composite. …”
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Embedded Meta evolutionary-firefly algorithm-ANN for multi dg planning in distribution system / Siti Rafidah Abdul Rahim
Published 2019“…This thesis presents a novel Embedded Meta Evolutionary–Firefly Algorithm-Artificial Neural Network for Multi-DG planning in distribution system. …”
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Thesis -
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Optimized feature construction methods for data summarizations of relational data
Published 2014“…Many approaches have been developed to discover knowledge (i.e. useful information) from data stored in multiple tables in a relational database. …”
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Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman
Published 2014“…The last part is the development of a metal artifact correction (MAC) algorithm and evaluation of the proposed algorithm in artifacts reduction in CT images. …”
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Monitoring the impacts of drought on land use/cover: a developed object-based algorithm for NOAA AVHRR time series data
Published 2011“…Primarily, raw weather data preparation activities were carried out to produce Standard Precipitation Index (SPI) spatial point thematic layer as a base map, then, satellite image pre-processing works applied on the remotely sensed data to generate the time series land use/cover maps. As a novel idea in this study, it developed a new object-based classification algorithm for AVHRR (Advanced Very High Resolution Radiometer) data. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Thesis -
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Sensorless control system for assistive robotic ankle-foot
Published 2018“…This article presents a novel sensorless control system of assistive robotic ankle-foot prosthesis, two estimation algorithms were developed and an analogy between them has been made. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Tree-based contrast subspace mining method
Published 2020“…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Multi-horizon ternary time series forecasting
Published 2013“…This paper proposes a novel multi-horizon ternary forecasting algorithm that forecasts whether a time series is heading for an uptrend or downtrend, or going sideways. …”
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Proceeding Paper -
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…However, machine and deep learning methods have higher accuracy but rely heavily on the quality and amount of training data, and the solution may become inconclusive if data is sparse. In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
Published 2020“…This problem inspires the idea to develop a prediction algorithm to predict the missing values in the dataset, where Support vector regression (SVR) has been proposed as a prediction method to predict missing values in several academic types of researches. …”
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