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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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A hybrid intelligent algorithm for solving the bilevel programming models
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A Constraint Programming-based Genetic Algorithm (CPGA) for Capacity Output Optimization
Published 2014“…Purpose: The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Genetic programming based machine learning in classifying public-private partnerships investor intention / Ahmad Amin ... [et al.]
Published 2023“…The PPP data was analyzed in this study using two machine learning approaches, Genetic Programming and conventional machine learning, with testing results showing that all machine learning algorithms from both approaches achieved high accuracy rates of over 80%, with the Genetic Programming machine learning outperformed the conventional approach. …”
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Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming
Published 2012“…By using FSM to describe the behaviour of a navigating mobile robot, an equivalent algorithm can be developed. The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Development of a cost efficient vision system for defects detection / Muhammad Zarif Kamarudin
Published 2010“…In this project, MATLAB platform is used to program the entire algorithm furthermore implementing Graphical User Interface to communicate between the vision system and the user. …”
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System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO)
Published 2022“…Program system assigns user tasks to the suitable Virtual Machines in order to attain Quality of Service (QoS) parameters. …”
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A new domain specific scripting language for automated machine learning pipeline
Published 2019“…In light of this situation, automated machine learning pipeline is highly beneficial. Research has proved that Genetic Programming is highly useful to find the best pipeline of an automated machine learning model. …”
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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm
Published 2023“…Biomass; Catalysis; Digital storage; Gasification; Gaussian distribution; Hydrogen production; Learning algorithms; Lime; Palm oil; Quadratic programming; Regression analysis; Sensitivity analysis; Synthesis gas; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Non-linear response; Performance; Quadratic modeling; Renewable energies; Support vectors machine; Syn gas; Support vector machines…”
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MAZE ROBOT: APPLYING AUTONOMOUS VEHICLE NAVIGATION ALGORITHM WITH EVENT-DRIVEN PROGRAMMING
Published 2011“…The basic navigation algorithm was developed using finite state machine (FSM). …”
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Control algorithm for two-tank system using multiparametric programming
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Reference-pulse CNC parametric curve real-time interpolator parallel algorithm using parallel programming
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed co-gasification of biomass wastes from oil palm
Published 2022“…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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