Search Results - intelligence based ((data algorithm) OR (((bees algorithm) OR (new algorithm))))
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Application of Bee Colony Optimization (BCO) in NP-Hard Problems
Published 2011“…Bee-Inspired algorithms were presumed to bring the new direction in the field of Swann Intelligence. …”
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Final Year Project -
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
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Performance Enhancement Of Artificial Bee Colony Optimization Algorithm
Published 2013“…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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A quick gbest guided artificial bee colony algorithm for stock market prices prediction
Published 2018“…In this respect, in the present manuscript, we propose an algorithm based on ABC to minimize the error in the trend and actual values by using the hybrid technique based on neural network and artificial intelligence. …”
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Artificial bee colony for inventory routing problem with backordering
Published 2014“…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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Machine Learning and Dyslexia-Diagnostic and Classification System (DCS) for Kids with Learning Disabilities
Published 2018“…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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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim
Published 2021“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Final Year Project -
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Time series forecasting of energy commodity using grey wolf optimizer
Published 2015“…The ability to model and perform decision making is an essential feature of many real-world applications including the forecasting of commodity prices.In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting.The model is built upon data obtained from the West Texas Intermediate (WTI) crude oil and gasoline price.Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE).Results showed that the GWO model outperformed DE in both crude oil and gasoline price forecasting. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
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.…”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…There exist many intelligent tools, which try to learn from the patterns in the data in order to predict classes of new data. …”
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A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems
Published 2019“…The average monthly demand for irrigation is 142.14 (106 m3), and the amount of released water based on the new hybrid algorithm (NHA) is 141.25 (106 m3). …”
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Time Series Forecasting of Energy Commodity using Grey Wolf Optimizer
Published 2015“…Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE). …”
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Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging
Published 2016“…Performance evaluations based on hit rate and byte hit rate for the new method over conventional methods with real data will be conducted for validation and verification…”
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Backpropagation neural network based on local search strategy and enhanced multi-objective evolutionary algorithm for breast cancer diagnosis
Published 2019“…However, the performance of such methods is based on the algorithms or technique. In this paper, we develop an intelligent technique using multiobjective evolutionary method hybrid with a local search approach to enhance the backpropagation neural network. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…The second improvement includes the development and use of new Local Search Algorithm with SSA to improve its exploitation. …”
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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