Search Results - (( variable optimization path algorithm ) OR ( _ classification modified algorithm ))
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1
The Implementation of Genetic Algorithm in Path Optimization
Published 2005“…Therefore, the implementation ofGA in path optimization can be ascertained offering a compelling result.…”
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Final Year Project -
2
Path optimization using genetic algorithm in laser scanning system
Published 2008“…In this paper, the genetic algorithm (GA) has been proposed to optimize the scanning sequence, thus shortening the required laser scanning path. …”
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3
Path optimization using genetic algorithm in laser scanning system
Published 2023Subjects:Conference paper -
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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5
Systematic design of chemical reactors with multiple stages via multi-objective optimization approach
Published 2015“…Following the identification of path-dependent design variables, several (possibly conflicting) design objectives will be selected and solutions of the corresponding problem will be generated from multi-objective optimization algorithm. …”
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6
Runtime reduction in optimal multi-query sampling-based motion planning
Published 2023Conference Paper -
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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
Published 2014“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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9
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…In addition, a contextual text classification experiment is conducted using benchmarked datasets to assess the performance of the modified word vectors in the targeted classification task. …”
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10
A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification
Published 2010“…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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11
A hybrid-based modified adaptive fuzzy inference engine for pattern classification
Published 2011“…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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12
Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…This work proposed the implementation of modified Artificial Bee Colony with Firefly algorithm for training the FLNN network to overcome the drawback of BP-learning algorithm. …”
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13
A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains
Published 2023“…However, these approaches only focus on one single objective, i.e. path optimality, path safety, efficiency or trajectory smoothness. …”
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14
Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification
Published 2022“…The new binary algorithms, BPSO, BGWOA, BWOA, BHHO, and BMRFO algorithms are utilized for solving the descriptors selection problem in supervised Amphetamine-type Stimulants (ATS) drug classification task. …”
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15
An Improved Wavelet Neural Network For Classification And Function Approximation
Published 2011“…The modified WNN was then applied in the areas of classification and function approximation.…”
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16
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2013“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
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18
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
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19
Literature Review of Optimization Techniques for Chatter Suppression In Machining
Published 2011“…In this paper, it can be observed that for chatter suppression, optimization focuses on spindle design, tool path, cutting process, and variable pitch. …”
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Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network
Published 2010“…Here, a routing tree is constructed based on the energy/bit minimization routing (EbMR). This algorithm looks for a short path from the subscriber station (SS) node to BS, while the optimal path is achieved when the whole path has the lowest EbMR. …”
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