Search Results - intelligence based ((((force algorithm) OR (swarm algorithm))) OR (model algorithm))

Search alternatives:

Refine Results
  1. 1

    Prediction of Optimum Cutting Conditions in Dry Turning Operations of S45C Mild Steel using AIS and PSO Intelligent Algorithm by Minhat, Mohamad, Abd Rahman, Md Nizam, Abbas, Adnan Jameel

    Published 2014
    “…The suggested system is based on Particle Swarm Optimization (PSO) and Artificial Immune System (AIS) intelligent algorithms. …”
    Get full text
    Get full text
    Conference or Workshop Item
  2. 2
  3. 3
  4. 4

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
    Get full text
    Get full text
    Thesis
  5. 5

    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

    Published 2019
    “…According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
    Get full text
    Get full text
    Monograph
  6. 6

    Development of a robust intelligent controller for a semi-active car suspension system by Abas, Hesham Ahmed Abdul Mutleba

    Published 2022
    “…Commonly, the Fuzzy rules are optimized using offline optimization methods such as Differential Evolutionary (DE), Particle Swarms Optimization (PSO), or Artificial Neural Network (ANN) algorithms. …”
    Get full text
    Get full text
    Thesis
  7. 7

    The Control of an Upper-Limb Exoskeleton by Means of a Particle Swarm Optimised Active Force Control for Motor Recovery by Anwar, P. P. Abdul Majeed, Zahari, Taha, Ismail, Mohd Khairuddin, Mohd Yashim, Wong Paul Tze, Muhammad Amirul, Abdullah, Mohd Azraai, M. Razman

    Published 2017
    “…A proportionalderivative (PD) architecture is employed to investigate its efficacy in performing joint-space control objectives namely the flexion/extension of the elbow joint as well as the forward adduction/abduction on the shoulder joint. An intelligent active force control (AFC) optimised by means of the Particle Swarm Optimisation (PSO) algorithm is also incorporated into the aforementioned controller to examine its effectiveness in compensating disturbances. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8

    Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption by Alsammak I.L.H., Mahmoud M.A., Gunasekaran S.S., Ahmed A.N., Alkilabi M.

    Published 2024
    “…Therefore, this study presents a new model based on the principles of nature-inspired metaheuristics that uses Swarm Intelligence (SI) to test the effectiveness of using an autonomous and decentralized behaviour for a swarm of Unmanned Aerial Vehicles (UAVs) or drones to detect all distributed fire spots and extinguishing them cooperatively. …”
    Article
  9. 9

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…Swarm intelligence algorithms are metaheuristic algorithms inspired by the simple interactions of biological organisms in a population. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Multi agent quality of service routing based on scheme ant colony optimization algorithm by Baygi, Maassoumeh Javadi

    Published 2014
    “…The important new aspect of ACR-QoS is the combination of constraint-based routing and DiffServ architecture, in Swarm Intelligence (SI) structure where a set of artificial ants is used to determine the optimal path for each class to construct class-based routing tables. …”
    Get full text
    Get full text
    Thesis
  11. 11
  12. 12

    Performance Comparison Of Intelligent Tuning Methods Using Pid-Afcga And Pid-Afcpso In Attenuating The Vibration Of The Suspended Handle Model by Choo, Kinn

    Published 2021
    “…Thus, several tuning methods such as crude approximation (CA), genetic algorithm (GA) and particle swarm optimization (PSO) are implemented and compared based on the performance of the suspended handle model under different vibration. …”
    Get full text
    Get full text
    Monograph
  13. 13

    Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications by O. F. Alijla, Basem

    Published 2015
    “…Pertama, algoritma TAC yang diubahsuai, diperkenalkan. The Intelligent Water Drop (IWD) algorithm is a swarm-based model that is useful for undertaking optimization problems. …”
    Get full text
    Get full text
    Thesis
  14. 14

    Dengue outbreak prediction using an improved salp swarm algorithm by Khairunnisa Amalina, Mohd Rosli, Zuriani, Mustaffa, Yuhanis, Yusof, Mohamad Farhan, Mohamad Mohsin

    Published 2020
    “…The research includes study using Swarm Intelligence (SI) algorithm. In this study, an improved Salp Swarm Algorithm (iSSA) is proposed for dengue outbreak prediction. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  15. 15

    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    Published 2014
    “…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  16. 16
  17. 17

    Methane plume localization with enhanced self-best reduction and Gaussian improved particle swarm optimization (GiPSO) by Liew, Jia Hun

    Published 2024
    “…Secondly, our research questions how the Gaussian gas plume model can address the adaptation of swarm intelligence in drone-based gas leakage detection. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

    Published 2011
    “…However, the non-model based AVC algorithms are faster than their model-based AVC counterparts.…”
    Get full text
    Get full text
    Thesis
  19. 19
  20. 20