Search Results - (( based evaluation from algorithm ) OR ( (parameter OR parameters) information based algorithm ))
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1
Aco-based feature selection algorithm for classification
Published 2022“…The performance of the proposed algorithm was evaluated on 18 benchmark datasets from the University California Irvine (UCI) repository and nine (9) deoxyribonucleic acid (DNA) microarray datasets against 15 benchmark metaheuristic algorithms. …”
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2
DESIGN OF ADAPTIVE BACKSTEPPING WITH GRAVITATIONAL SEARCH ALGORITHM FOR NONLINEAR SYSTEM
Published 2014“…Performance evaluation is observed based on the tracking output and the tracking error between reference input and the system’s output. …”
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3
Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria
Published 2021“…This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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4
An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…In this study, a fully online density-based clustering algorithm called Buffer-based Online Clustering for Evolving Data Stream (BOCEDS) is presented. …”
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5
Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria
Published 2021“…This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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6
Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
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7
A combinatory algorithm of univariate and multivariate gene selection
Published 2009“…In this paper, we considered new parameters which come up from singular value decomposition and present a combination algorithm for gene selection to integrate the univariate and multivariate approaches and compare it with gene selection based on correlation coefficient with binary output classes to analyze the effect of new parameters. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…The motion planning problem poses the question of how a robot can move from an initial to a final position. Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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10
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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A comparative study for parameter selection in online auctions
Published 2009“…Due to the complex and dynamic nature of the online auction, one of the strategies employed is using genetic algorithm to discover the best strategy. Hence, this work attempts to improve an existing bidding strategy by taking into accounts the evolution of various model of generic algorithm in optimizing the parameter of the bidding strategies. …”
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12
Contrast enhancement for colour images based on discrete wavelet transform
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Student Project -
13
Identification of the thermoelectric cooler using hybrid multi-verse optimizer and sine cosine algorithm based continuous-time Hammerstein model
Published 2021“…The efficiency of the proposed method is evaluated based on the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon’s rank test. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Thus, this thesis has developed and evaluated a filter based Information Theoretic-based Feature Selection (IFS) for machine learning. …”
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15
Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Second, propose an Optimized Time Sliding Window based Three Colour Marker. Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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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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17
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The NPO was tested and evaluated based on sixty unconstrained benchmark test functions. …”
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18
Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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Book Chapter -
19
The normalized random map of gradient for generating multifocus image fusion
Published 2020“…It successes to eliminate the mathematical and algorithm problems. Furthermore, the evaluation of proposed method based on the fused image quality. …”
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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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