Search Results - (( intelligence based three algorithm ) OR ( intelligence based bee algorithm ))

Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. …”
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Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

“…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

“…A total of 6 datasets were deployed to evaluate the effectiveness of the proposed algorithm. Results showed that EACS(TS) outperformed in terms of success rate, packet loss, latency, and energy efficiency when compared with single swarm intelligence routing algorithms which are Energy-Efficient Ant-Based Routing (EEABR), BeeSensor and Termite-hill. …”
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Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation by Alazzawi, A.K., Rais, H.M., Basri, S.

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Artificial bee colony for inventory routing problem with backordering by Moin, N.H., Halim, H.Z.A.

“…We propose a metaheuristic method, Artificial Bee Colony (ABC) to solve the IRPB.The ABCalgorithm is a swarm based heuristics which simulates the intelligent foraging behaviour of a honey bee swarm and sharing that information of the food sources with the bees in the nest. …”
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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.…”
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An Intelligent Modeling of Oil Consumption by Chiroma, Haruna, Abdulkareem, Sameem, Muaz, Sanah Abdullahi, Abubakar, Adamu I., Sutoyo, Edi, Mungad , Mungad, Saadi, Younes, Sari, Eka Novita, Tutut, Herawan

“…In this study, we select Middle East countries involving Jordan, Lebanon, Oman, and Saudi Arabia for modeling oil consumption based on computational intelligence methods. The limitations associated with Levenberg-Marquardt (LM) Neural Network (NN) motivated this research to optimize the parameters of NN through Artificial Bee Colony Algorithm (ABC-LM) to build a model for the prediction of oil consumption. …”
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A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting by Ibrahim K.S.M.H., Huang Y.F., Ahmed A.N., Koo C.H., El-Shafie A.

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. To address swarm intelligence adaptation in drone-based gas leakage detection, we investigate the existing swarm intelligence capability in optimizing dynamical problems in gas plume detection. …”
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A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali by Mohamed Kamali, Mohd Zahurin

“…In- stead of a sophisticated controller that governs the global behavior of the system, the swarm intelligence principle is based on many unsophisticated entities (for example such as ants, termites, bees etc.) that cooperate and interact in order to exhibit a desired behav- ior. …”
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An efficient multi join query optimization for relational database management system using swarm intelligence approaches by Alsaedi, Ahmed Khalaf Zager

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An efficient multi join query optimization for relational database management system using swarm intelligence approaches by Alsaedi, Ahmed Khalaf Zager

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Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy by Hossain Md.S., El-Shafie A., Mohtar W.H.M.W.

Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed by Mudasir , Ahmed

“…The preliminary review of existing control techniques revealed that the Bio-inspired intelligent algorithms (BIAs) based selective harmonic elimination pulse width modulation (SHEPWM) are more proficient to eliminate the loworder harmonics. …”
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

“…The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

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Artificial intelligence in sustainability reporting / Prof. Dr Corina Joseph by Joseph, Corina

“…Corina delivering her speech titled "AI and SDGs: Resource-Based View Perspective." In the speech introduction, various definitions of Artificial Intelligence (AI) were provided. …”
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Hybrid Sine Cosine and Fitness Dependent Optimizer for global optimization by Chiu, Po Chan, Ali, Selamat, Ondrej, Krejcar, Kuok, King Kuok

“…The fitness-dependent optimizer (FDO), a newly proposed swarm intelligent algorithm, is focused on the reproductive mechanism of bee swarming and collective decision-making. …”
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Application of Bee Colony Optimization (BCO) in NP-Hard Problems by Kamarudin, Muhammad Sariy Syazwan

“…Bee-Inspired algorithms were presumed to bring the new direction in the field of Swann Intelligence. …”
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Machine Learning and Dyslexia-Diagnostic and Classification System (DCS) for Kids with Learning Disabilities by Rehman Ullah, Khan, Julia Ai Cheng, Lee, Oon, Yin Bee

“…Most experts are using manual techniques to diagnose dyslexia. Machine learning algorithms are capable enough to learn the knowledge of experts and intelligently diagnose and classify dyslexics. …”
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