Search Results - (( course evaluation study algorithm ) OR ( parameters variation inspired algorithm ))*
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control
Published 2025“…The performance of the proposed approach was extensively benchmarked against four modern metaheuristic algorithms (greater cane rat algorithm, catch fish optimization algorithm, RIME algorithm and artificial hummingbird algorithm) under identical conditions. …”
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A modified technique in RFID networking planning and optimization
Published 2015“…The solution typically inspired by nature includes the use of Genetic Algorithm (GA), Bacteria Foraging Optimization (BFO) and Particle Swarm Optimization (PSO) Algorithm. …”
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Imitation of honeybee aggregation with collective behavior of swarm robots
Published 2011“…This aggregation is implemented based on variation of parameters values. In the second phase, two modifications on original honeybee aggregation namely dynamic velocity and comparative waiting time are proposed. …”
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Using algorithmic taxonomy to evaluate lecturer workload
Published 2006“…The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset. Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal
Published 2006“…The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset. Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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Automated study plan generator using rule-based and knapsack problem
Published 2022“…Hence, this study aims to propose an algorithm to generate an automated and accurate study plan throughout the study duration. …”
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Evaluate the performance of university course timetabling problem with different combinations of genetic algorithm
Published 2025“…University course timetabling problem (UCTP) is a scheduling problem that requires courses to be assigned to the limited time slots, classrooms, and lecturers, while adhering to a set of predefined constraints. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal
Published 2006“…Lecturer workload at universities includes three major categories: teaching, research and services.Teaching workload is influence by various factors such as level taught courses, number of student, credit and contact hour and off campus or on campus course design.The UPM has a KM Portal that contains sets of metadata on lecturer profile and knowledge assets.The Lecturer profile contains information lecturer teaching, research, publication and many more.We constructed an algorithmic taxonomy based at the lecturer profile data to measure lecturer teaching workload.This method measures the lecturer teaching workload.The taxonomy is a dynamic hierarchy that extracts validated parameters from the dataset.Results of the study highlight the contributions of this algorithmic method in better evaluation of teaching workload for lecture.…”
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PSO-tuned pid sliding surface of sliding mode control for an electro-hydraulic actuator system
Published 2017“…Then, the PSO, which is based on the inspiration of the swarming behaviour has been utilized to seek for the optimum PID sliding surface parameters. …”
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Enhanced stability and performance of the tidal energy conversion system using adaptive optimum relation-based MPPT algorithms
Published 2025“…The A-ORB algorithm integrates the optimum relation-based (ORB) approach with Hill Climb Search (HCS), along with an adaptive gain adjustment mechanism that dynamically tunes the parameter K based on power variation (ΔP). …”
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An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…The variations of second order optimisation methods have been proposed which provide less iteration of convergence. …”
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Using web questionnaire for web-based course evaluation: advantages and disadvantages
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…Data for the study was collected from university records, and algorithm performance was tested against predefined scheduling criteria. …”
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Prediction of MUET result based on KNN algorithm / Siti Fatimah Azzahra Hamrizan
Published 2021“…The exam results from the ELC can be the features to help the students to know if they can pass the MUET exam and the lecturers can figure out which language skills need to be improved to help preparing the students to sit for MUET. The study aims to explore the K-Nearest Neighbour (KNN) algorithm in solving the MUET result prediction problem, to develop a prototype of MUET result prediction based on the KNN algorithm and to evaluate the accuracy of the KNN algorithm in MUET result prediction. …”
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