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

Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning of PID Controller in Industrial Couple Tank System by Ismail, Mohd Khairuddin, Amira Sarayati, Ahmad Dahalan, Amar Faiz, Zainal Abidin, Yee, Yang Lai, Nur Anis, Nordin, Siti Fatimah, Sulaiman, Hazriq Izzuan, Jaafar, Syahrul Hisham, Mohamad, Noor Hafizah, Amer

“…These swarm intelligence algorithms are Particle Swarm Optimization (PSO) and Firefly Algorithm (FA). …”
Get full text
Get full text
Get full text

Modeling and Simulation of Swarm Intelligence Algorithms for Parameters Tuning Of PID Controller in Industrial Couple Tank System by Mohd Khairuddin, Ismail, Ahmad Dahalan, Amira Sarayati, Zainal Abidin, Amar Faiz, Yee, Yang Lai, Nordin, Nur Anis, Siti Fatimah, Sulaiman, Jaafar, Hazriq Izzuan, Mohamad, Syahrul Hisham, Amer, Noor Hafizah

“…These swarm intelligence algorithms are Particle Swarm Optimization (PSO) and Firefly Algorithm (FA). …”
Get full text
Get full text

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

“…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

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

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

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

“…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

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.

“…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. …”

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

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

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

“…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

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

“…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

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

“…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

Joint torque estimation model of surface electromyography(sEMG) based on swarm intelligence algorithm for robotic assistive device by Nurhanim, K., Elamvazuthi, I., Vasant, P., Ganesan, T., Parasuraman, S., Ahamed Khan, M.K.A.

Get full text
Get full text

INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM by Muhammad Hasbollah, Hassan

Get full text
Get full text

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
Get full text
Get full text
Get full text

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

“…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

Intelligent Prediction System for Gas Metering System using Particle Swarm Optimization in Training Neural Network by Rosli, N.S., Ibrahim, R., Ismail, I.

“…Then the project focused on the application of particle swarm optimization (PSO) and Genetic Algorithm (GA) in training neural network prediction model in enhancing the performance of Intelligent Prediction System (IPS). …”
Get full text
Get full text

A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems by Yaseen, Zaher, Ehteram, Mohammad, Hossain, Md., Fai, Chow, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, Lai, Sai Hin, Zaini, Nuratiah, Ahmed, Ali, El-Shafie, Ahmed

“…Power production utilizing the NHA's operation rule achieved a sufficient magnitude relative to that of stand-alone models, such as the BA, PSO, WA, SA, and GA. The excellent proficiency of the developed intelligence expert system is the result of the hybrid structure of the BA and PSO algorithm and the substitution of weaker solutions in each algorithm with better solutions from other algorithms. …”
Get full text
Get full text

Advances in Particle Swarm Algorithms in Asynchronous, Discrete and Multi-Objective Optimization by Zuwairie, Ibrahim

Get full text
Get full text
Get full text

MARKERLESS ARTICULATED HUMAN MOTION TRACKING USING HIERARCHICAL MULTI-SWARM COOPERATIVE PARTICLE SWARM OPTIMIZATION by SAINI, SANJA Y

“…Most recently. the swarm-intelligence based PSO algorithm have been gaining momentum in this tield.…”
Get full text
Get full text

African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

“…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
Get full text
Get full text
Get full text

A novel hybrid evolutionary data-intelligence algorithm for irrigation and power production management: Application to multi-purpose reservoir systems by Yaseen Z.M., Ehteram M., Hossain M.S., Fai C.M., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., Hin L.S., Zaini N., Ahmed A.N., El-Shafie A.