Among most machine learning algorithms for optimization problem including meta-heuristic search algorithms, the solution is drawn like a moth to a flame and cannot keep away. The track of chaotic variable can travel ergodically over the whole search space. In general, the chaotic variable has special characters, i.e., ergodicity, pseudo-randomness and irregularity. To enrich the searching behav...

This research work intends to propose a system with improved cuckoo searchbased robust ensemble co-clustering algorithm (ICS RECCA) for enzyme clustering. The cuckoo search algorithm has been inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds (of other species). Some host birds can engage direct conflict with the intruding cuck...

Hard optimization problems that cannot be solved within reasonable time by standard, mathematical, deterministic methods are of great practical interest. Metaheuristics inspired by nature were recently successfully used for such problems. These metaheuristics are based on random Monte-Carlo search guided by simulation of some nature intelligence, especially evolution and swarm intelligence. One...

Optimal power flow is the most complicated economical problem in power system operation. This is due to the nonlinearity of load flow equations and constraints on voltage, thermal limits and angle and voltage stability. The objective of this problem is to distribute system loads among generators with minimum cost while achieving all equality and inequality constraints. Nowadays, meta heuristic ...

Software testing is a very important phase in the development of software. Testing includes the generation of test cases which, if done manually, is time consuming. To automate this process and generate optimal test cases, several meta-heuristic techniques have been developed. These approaches include genetic algorithm, cuckoo search, tabu search, intelligent water drop, etc. This paper present...

In order to improve convergence velocity and optimization accuracy of the cuckoo search (CS) algorithm for solving the function optimization problems, a new improved cuckoo search algorithm based on the repeat-cycle asymptotic self-learning and self-evolving disturbance (RC-SSCS) is proposed. A disturbance operation is added into the algorithm by constructing a disturbance factor to make a more...

─ Cuckoo Search (CS) is a new met heuristic algorithm. It is being used for solving optimization problem. It was developed in 2009 by XinShe Yang and Susah Deb. Uniqueness of this algorithm is the obligatory brood parasitism behavior of some cuckoo species along with the Levy Flight behavior of some birds and fruit flies. Cuckoo Hashing to Modified CS have also been discussed in this paper. CS ...

Today’s world sees a lot of changes being done. These are a result of some modification or some innovation. This research is being done in the field of Swarm Intelligence or SI. It deals with studying the behaviour of organisms or swarms. Swarms are individual entities which are working on their own, yet their combined or aggregate behaviour yields some great results. This begins by studying th...

Today, with rapid growth of the World Wide Web and creation of Internet sites and online text resources, text summarization issue is highly attended by various researchers. Extractive-based text summarization is an important summarization method which is included of selecting the top representative sentences from the input document. When, we are facing into large data volume documents, the extr...