Search Results - (( variable optimization path algorithm ) OR ( _ classification modified algorithm ))

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  1. 1

    The Implementation of Genetic Algorithm in Path Optimization by Jumali, Suriana

    Published 2005
    “…Therefore, the implementation ofGA in path optimization can be ascertained offering a compelling result.…”
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    Final Year Project
  2. 2

    Path optimization using genetic algorithm in laser scanning system by Chen, Chai Phing, Koh, Johnny Siaw Paw, Aris, Ishak, Fong, Albert Yu Chooi, Tiong, Sieh Kiong

    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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    Conference or Workshop Item
  3. 3
  4. 4

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    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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    Thesis
  5. 5

    Systematic design of chemical reactors with multiple stages via multi-objective optimization approach by Mohd Fuad, Mohd Nazri, Hussain, Mohd Azlan

    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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    Conference or Workshop Item
  6. 6
  7. 7

    The use of SOM for fingerprint classification by Turky A.M., Ahmad M.S.

    Published 2023
    Subjects:
    Conference paper
  8. 8

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    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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    Article
  9. 9

    Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

    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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    Thesis
  10. 10

    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

    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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    Article
  11. 11

    A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

    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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    Conference or Workshop Item
  12. 12

    Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

    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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    Thesis
  13. 13

    A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

    Published 2023
    “…However, these approaches only focus on one single objective, i.e. path optimality, path safety, efficiency or trajectory smoothness. …”
    Article
  14. 14

    Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification by Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

    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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    Article
  15. 15

    An Improved Wavelet Neural Network For Classification And Function Approximation by Ong , Pauline

    Published 2011
    “…The modified WNN was then applied in the areas of classification and function approximation.…”
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    Thesis
  16. 16

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Yana Mazwin Mohmad Hassim, Rozaida Ghazali

    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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    Article
  17. 17

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    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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    Article
  18. 18

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    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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    Article
  19. 19

    Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

    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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    Article
  20. 20

    Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network by Qasem, Yaaqob Ali Ahmed

    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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    Thesis