Search Results - (( _ constructive path algorithm ) OR ( using optimization learning algorithm ))

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  1. 1

    Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

    Published 2017
    “…Finally, the last objective is to improve the optimality of the new approach using a robust Machine Learning strategy. …”
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    Thesis
  2. 2

    The duality of technological innovation and dynamic capabilities: the micro-foundation of China's construction machinery industry's rise up the global value chain by Xia, Weifu, Alwie, Aryaty, Taasim, Shairil Izwan, Jin, Wong Tze, Naning, Fatin Hana

    Published 2024
    “…Based on organizational learning theory and dynamic capability perspective, this study constructs a theoretical framework of dual integration of technological innovation (exploratory innovation and pioneering innovation) and dynamic capability, and explores its impact mechanism on the global value chain upgrading of Chinese construction machinery enterprises. …”
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    Article
  3. 3

    A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

    Published 2022
    “…The suggested algorithm outperforms the competition in terms of improving path cost, smoothness, and search time. …”
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    Thesis
  4. 4

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

    Published 2013
    “…Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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  5. 5

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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    Article
  6. 6

    Route optimization using shortest path method / Muhamad Faisal Amin Shakri by Shakri, Muhamad Faisal Amin

    Published 2025
    “…This study investigated the implementation and comparison between well known shortest path method which are Dijkstra’s algorithm, Bellman-Ford, and A* algorithm. …”
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    Thesis
  7. 7

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
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  8. 8

    Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff by Sariff, Nohaidda

    Published 2011
    “…In the initial stage, the test environments were constructed. Subsequently, both algorithms were applied to the test environments. …”
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  9. 9
  10. 10

    Wi-fi fingerprint database construction using Chebyshev wavelet functions by Narzullaev, Anvar, Nemadaliev, Azamjon, Selamat, Mohd Hasan, Othman, Mohamed, Sharif, Khaironi Yatim

    Published 2015
    “…Proposed algorithm combines the reference data collection procedure with path-loss prediction. …”
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    Conference or Workshop Item
  11. 11

    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

    Published 2014
    “…Backpropagation (BP) learning algorithm is the well-known learning technique that trained ANN. …”
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  12. 12
  13. 13

    An efficient algorithm to improve oil-gas pipelines path by Hasan Almaalei, Nabeel Naeem, Mohd Razali, Siti Noor Asyikin, Mohammed Alduais, Nayef Abdulwahab

    Published 2018
    “…Therefore, the aim of this study is to propose a new algorithm to obtain the shortest path connecting oil-gas wells and addressing obstacles that may appear on the path connecting any two wells. …”
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    Article
  14. 14

    Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

    Published 2006
    “…To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weight optimization. …”
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  15. 15
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    Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

    Published 2023
    “…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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    Article
  17. 17

    Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm by Ullah, Wasif, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

    Published 2024
    “…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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    Article
  18. 18

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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    Article
  19. 19

    Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

    Published 2011
    “…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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    Thesis
  20. 20

    GIS mapping and shortest-path algorithm for drone-aided flood rescue operations by Schigdar, Ahmad, Zaman, Nafees, Hassan, Raini

    Published 2019
    “…This research aims to implement Geographic Information System (GIS) mapping to identify the major parts of an affected state that are more susceptible to floods and the construction of an optimal shortest path algorithm to conduct the rescue operation.…”
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    Proceeding Paper