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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…However, there needs to be more research examining the role of interactive methods in multiobjective optimisation problems. To integrate machine learning and human interactions, this paper develops a new three-stage interactive algorithm in business analytics, called the interactive Nautilus-based algorithm, to address complex problems. …”
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…In this research, we showed how evolutionary multi-objective algorithms can be used to solve the view selection problem and its advantage over classical optimization problems were described. …”
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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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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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Linear quadratic regulator with genetic algorithm for flexible structures vibration control
Published 2015“…The comprehensive account is given by way of a generic example with the solution of LQR problem using genetic algorithm for this structure. …”
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A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
Published 2019“…In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amount of energy, especially during the training phase. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Practical implications In terms of managerial implications, the findings in this research help to frame the adoption of a more advanced analytical approach to forecasting, using a Machine Learning algorithm, in solving a newsvendor problem. …”
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Book Section -
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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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Predictive Analytics in Genetic Engineering as an Optimization Problem
Published 2024“…The nature of the problem requires that a stochastic optimization algorithm be applied in the metaheuristic search rather than using a deterministic or mathematical approach. …”
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Analytic Hierarchy Process Decision Making Algorithm
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A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption
Published 2019“…In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amount of energy, especially during the training phase. …”
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Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms
Published 2024“…On the other hand, machine learning (ML) has made it possible to employ a variety of approaches for mechanical and aerospace problems and such significant approach is the repair mechanism and hence ML algorithms used to enhance in the present work. …”
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Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems
Published 2019“…In this algorithm, the convolution theorem has been used to find an optimal Lagrange multiplier.…”
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Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems
Published 2019“…In this algorithm, the convolution theorem has been used to find an optimal Lagrange multiplier.…”
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An algorithm for positive solution of boundary value problems of nonlinear fractional differential equations by Adomian decomposition method
Published 2016“…In the proposed algorithm the boundary conditions are used to convert the nonlinear fractional differential equations to an equivalent integral equation and then a recursion scheme is used to obtain the analytical solution components without the use of undetermined coefficients. …”
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Solving New Student Allocation Problem (NSAP) With Analytical Hierarchy Process (AHP)
Published 2014“…There are many approaches used to solve New Student Allocation Problem (NSAP).Many researchers use application of Genetic Algorithm (GA).However,the study presented in this paper applies an Analytical Hierarchy Process (AHP)technique in solving New Student Allocation Problem (NSAP) handled by Registration Unit at Ungku Omar Polytechnic.The problem is the students are allocated to their class randomly,just by using their registration number and by all means without referring to their intelligence level,knowledge,skills and also their performance.So,in this paper the researcher’s focus is on solving NSAP by using AHP to allocate students into their respective classes with minimum intelligence gap in each class and the number of students in each class does not exceed its maximum capacity.The proposed solution will be tested using real data from the Politeknik Ungku Omar to see the result. …”
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Flower pollination algorithm for data generation and analytics - a diagnostic analysis
Published 2020“…The effectiveness of optimization in scientific and engineering applications has made optimization a popular area of scientific investigation in data generation and analytics leading to the design of several optimization algorithms. …”
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