optimal sitting and sizing of shunt capacitor banks at the distribution networks for the purpose of power quality improvement is drawn much attention of electric power utilities in the last decades. determining the optimal number, location and sizing of capacitor using bee colony optimization algorithm (bco) is being presented in this paper. the bco algorithm is a new population based meta-heur...

Design a new novel intelligence algorithm which is called as chaotic quantum bee colony optimization (CQBCO) for discrete optimization problem. The proposed CQBCO applies the chaotic theory to quantum bee colony optimization (QBCO), which is an effective discrete optimization algorithm. Then the proposed chaotic quantum bee colony algorithm is used to solve benchmark functions and optimization ...

The identification of values of solar cell parameters is of great interest for evaluating solar cell performances. The algorithm of an artificial bee colony was used to extract model parameters of solar cells from current-voltage characteristics. Firstly, the best-so-for mechanism was introduced to the original artificial bee colony. Then, a method was proposed to identify parameters for a sing...

The most common way to enforce access control is user authentication based on username and password. This form of access control has many flaws which make it vulnerable to hacking. Biometric authentication such as the keystroke dynamics is used in which the keyboard is used in order to identify users. Then the classifier is tailored to each user to find out whether the given user is genuine or ...

In this paper, the previously proposed Predictive Energy Efficient Bee-inspired Routing (PEEBR) family of routing optimization algorithms based on the Artificial Bees Colony (ABC) Optimization model is extended from a random static mobility model, as employed by its first version (PEEBR1), into a random mobility model in its second version (PEEBR2). This random mobility model used by PEEBR-2 al...

This study adapted an improved algorithm based on Artifical Bee Colony Optimization. It is not possible to justify that all the rules generated by fuzzy based apriori algorithm produce optimum result. Thus optimization of the result generated was carried out by Fuzzy Apriori algorithm using Fuzzy Artifical Bee Colony Optimization (FABCO), it's worth noting that a significant findings were revea...

-The paper deals with the concepts of expert system and data mining belongs to the Artificial Intelligence fields. The main task of expert system is to ratiocination, while the machine learning algorithm is to find the better optimal solution. This paper mainly focuses on diagnoses of the disease which is effected to the Emu bird by mechanism of Particle Swarm Optimization (PSO) algorithm and A...

Artificial Bee Colony (ABC) is a swarm optimization technique. This algorithm generally used to solve nonlinear and complex problems. ABC is one of the simplest and up to date population based probabilistic strategy for global optimization. Analogous to other population based algorithms, ABC also has some drawbacks computationally pricey due to its sluggish temperament of search procedure. The ...

Bio inspiration is a branch of artificial simulation science that shows pervasive contributions to variety of engineering fields such as automate pattern recognition, systematic fault detection and applied optimization. In this paper, a new metaheuristic optimizing algorithm that is the simulation of “The Great Salmon Run” (TGSR) is developed. The obtained results imply on the acceptable perfor...

The job shop scheduling problem (JSSP) is an NP-hard problem of wide engineering and theoretical background. In this paper, a discrete artificial bee colony based memetic algorithm, named DABC, is proposed for solving JSSP. Firstly, to make artificial bee colony (ABC) suitable for solving JSSP, we present a food source as a discrete job permutation and use the discrete operation to generate a n...