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Quarter-sweep preconditioned relaxation method, algorithm and efficiency analysis for fractional mathematical equation
Published 2021“…Research into the recent developments for solving fractional mathematical equations requires accurate and efficient numerical methods. …”
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A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer
Published 2024“…The recent development of knowledge in fractional calculus introduced an advanced superior operator known as fractal–fractional derivative (FFD). …”
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Computational approach via half-sweep and preconditioned aor for fractional diffusion
Published 2022“…The convergence of the developed method is analyzed. Finally, some numerical experiments from our research are given to illustrate the efficiency of our computational approach to solve the proposed problems of time-fractional diffusion. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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Conference or Workshop Item -
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Thesis -
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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…The major research findings were as follows: 1) the non-parametric and parametric estimation methods using the right and interval censoring types produced highly efficient cure rate parameters when the censoring rate was decreased to the minimum possible; 2) Non-parametric estimation of the cure fraction using interval censored data based on Turnbull estimator resulted in more precise cure fraction than the Kaplan Meier estimator considering the interval midpoint to represent the exact life time; 3) The parametric estimation of the cure fraction based on the exponential distribution and right and interval censoring types produced more consistent estimates than the Weibull distribution especially in case of heavy censoring; 4) Parametric estimation of the cure fraction was more efficient when some covariates had been involved in the analysis than when covariates had been excluded; and 5) the nonparametric estimation method is the viable alternative to the parametric one when the data set contains substantial censored observations while in the case of low censoring the parametric method is more attractive.…”
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Thesis -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Development of rule-based advisory system from modified hazard and operability study on fatty acid fractionation column
Published 2003“…A modified Hazard and Operability Study (HAZOP) algorithm has been proposed in order to develop process deviation relationships between two study nodes in HAZOP study. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Monograph -
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Parametric cure fraction models for interval-censoring with a change-point based on a covariate threshold
Published 2015“…Therefore, this study focuses on developing several classes of parametric survival cure models for interval-censored data incorporating a cure fraction and change-point effect in covariate. …”
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Fault detection and diagnosis using correlation coefficients
Published 2005“…A fractionation column from a palm oil fractionation plant is chosen as the case study and the model of the case study is simulated in Matlab. …”
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Multi-Objective Optimization of Solar Powered Irrigation System by Using Genetic Algorithm
Published 2015“…However, this complex system needs to be optimized by using suitable metaheuristic technique in order to make the design to be economically and practically efficient. Thus, Genetic Algorithm is applied to solve multiple objective solar-irrigation system optimization. …”
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Final Year Project -
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operato...
Published 2025“…The numerical examples demonstrated the efficiency of the proposed method in solving the complicated higher order fractional problems of linear and non-linear terms.…”
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An advanced scheme based on Artificial Intelligence technique for solving nonlinear Riccati systems
Published 2024“…A vectorization algorithm is designated for the selected step to make the computation process more efficient. …”
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Solar Photovoltaic Maximum Power Point Tracking via Predictive Technique
Published 2022“…The first stage of this study is to develop the MPPT algorithm that are commonly divided into six types; Perturb and Observe (P&O), Incremental Conductance (INC), Fractional Open Circuit Voltage (FOVC), Fractional Short Circuit Current (FSCC), Artificial Neural (ANN) and Fuzzy Logic Control (FLC). …”
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Final Year Project Report / IMRAD -
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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