Search Results - (( framework implementation learning algorithm ) OR ( parameter evaluation path algorithm ))
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1
Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
Conference paper -
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Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin
Published 2010“…Performances between both algorithms were compared and evaluated in terms of speed and number of iterations that each algorithm takes to find an optimal path within several selected environments. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Subjects:Conference Paper -
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A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Published 2023“…These parameters are designed carefully to cover different requirements of the path planner. …”
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…Subsequently, both algorithms were applied to the test environments. Finally, the performances of both algorithms were analyzed and evaluated based on the required criteria. …”
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7
An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town
Published 2005“…The objectives of this study are to explore and evaluate the Ant System (AS) algorithm and Ant Colony System (ACS) algorithm in finding shortest paths. …”
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8
Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation
Published 2021“…Due to this polarization effect, the brick-built type cabin at the DRG site is a consequence of a higher propagation path loss than the Iron (III)-made cabin. The other performance parameters, including network throughput, data loss, and ZigBeePRO collision, are also evaluated.…”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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Rapid software framework for the implementation of machine learning classification models
Published 2021“…This paper provides an insight of a rapid software framework for implementing machine learning. This paper also demonstrates the empirical research results of machine learning classification models from the rapid software framework. …”
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All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…The performance evaluation in terms of convergence speed of the proposed algorithm is validated with standard ANC without secondary path modelling. …”
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A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection
Published 2023“…The multi-agent system applies ant colony optimization and fuzzy logic search algorithms as tools to detecting learning styles. Ultimately, a working prototype will be developed to validate the framework using ant colony optimization and fuzzy logic. � 2013 Springer-Verlag.…”
Conference Paper -
13
Attack path selection optimization with adaptive genetic algorithms
Published 2016“…It calculates the appropriate adjustments for the control parameters such as selection and crossover rate. Possible attack paths are then identified and evaluated based on an attack graph representing the network under study. …”
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Attack path selection optimization with adaptive genetic algorithms
Published 2016“…It calculates the appropriate adjustments for the control parameters such as selection and crossover rate. Possible attack paths are then identified and evaluated based on an attack graph representing the network under study. …”
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15
Transmission path optimization Based on Efficiency Communication System
Published 2022“…At the same time, the developed algorithm combines the relative position of the cluster and the base station to further improve the routing method of the sub-cluster head, Finally, the algorithm analyzes the influence of different parameters on the transmission path, and use the simulation experiments to evaluate the conclusions.…”
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16
Implementing case-based reasoning approach to framework documentation
Published 2023“…Genetic algorithm (GA) is used in implementing the CBR's "retrieve", "reuse", and "revise" steps. …”
Conference paper -
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Interactive framework for dynamic modelling and active vibration control of flexible structures
Published 2008“…Controller-design strategies, parametric as well as nonparametric, are integrated within this framework. The design and implementation of the interactive learning system incorporating the simulation algorithms, modelling and control strategies, are developed using MATLAB. …”
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Real-Time Optimal Trajectory Correction (ROTC) for autonomous quadrotor / Noorfadzli Abdul Razak
Published 2018“…The algorithm works if the quadrotor undergoes a deviation, an admissible trajectory path is generated for the quadrotor rapidly return on the straight-line route. …”
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19
Genetic algorithm based ensemble framework for sentiment analysis
Published 2018“…Finally, the last experiment involves creating the complete optimized multilayered ensemble framework and implementation of the framework to find the suitable combination of methods in each layer to produce satisfactory sentiment analysis accuracy. …”
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20
Financial time series predicting using machine learning algorithms
Published 2013“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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