Back-propagation Neural Network (BPNN) algorithm is one of the most widely used and a popular technique to optimize the feed forward neural network training. Traditional BP algorithm has some drawbacks, such as getting stuck easily in local minima and slow speed of convergence. Nature inspired meta-heuristic algorithms provide derivative-free solution to optimize complex problems. This paper pr...

This paper deals with application of evolutionary algorithm (EA) to solve optimal power flow problem in an efficient manner. In this paper a new approach using cuckoo search (CS) method is proposed for solving OPF problem by optimal setting of control variables. Cuckoo search method is a bio-inspired algorithm based on brooding behaviour of cuckoo birds. This algorithm can search for a global s...

Cuckoo Search (CS) algorithm is a metaheuristic optimization algorithm developed by Xing-she Yang and Suash Deb in 2009. This paper explores the various research work done in application of Cuckoo Search algorithm in optimization of geometry, processes, signals and systems in real world engineering problems. Various researchers have applied Cuckoo Search algorithm in the following broad domains...

Cuckoo Search is one of the recent swarm itelligence metaheuritics. It has been succesfuly applied to a number of optimization problems, but is stil not very well researched. In this paper we present a parallelized version of the Cuckoo Search algorithm. The parallelization is implemented using CUDA architecture. The algorithm is significantly changed compared to the sequential version. Changes...

Disease forecasting using soft computing techniques is major area of research in data mining in recent years. To classify heart and diabetes diseases, this paper proposes a diagnosis system using cuckoo search optimized rough sets based attribute reduction and fuzzy logic system. The disease prediction is done as per the following steps 1) feature reduction using cuckoo search with rough set th...

In this paper, an improved method based on evolutionary algorithm for speech signal denoising is proposed. In this approach, the stochastic global optimization techniques such as Artificial Bee Colony(ABC), Cuckoo Search (CS)algorithm, and Particle Swarm Optimization (PSO) technique are exploited for learning the parameters of adaptive filtering function required for optimum performance. It was...

This paper proposes two novel nature inspired decision level fusion techniques, Cuckoo Search Decision Fusion (CSDF) and Improved Cuckoo Search Decision Fusion (ICSDF) for enhanced and refined extraction of terrain features from remote sensing data. The developed techniques derive their basis from a recently introduced bio-inspired meta-heuristic Cuckoo Search and modify it suitably to be used ...

Cuckoo search (CS) is a new robust swarm intelligence method that is based on the brood parasitism of some cuckoo species. In this paper, an improved hybrid encoding cuckoo search algorithm (ICS) with greedy strategy is put forward for solving 0-1 knapsack problems. First of all, for solving binary optimization problem with ICS, based on the idea of individual hybrid encoding, the cuckoo search...

Data classification is one of the major tasks in data mining that organizes data in the proper manner to provide enhanced functionality to extract useful information from that data. There are various supervised and unsupervised machine learning techniques like FNN (Fuzzy Neural Network) presented by the researchers to provide an enhanced classification of the dataset. But the performance of the...

RNA secondary structure prediction uses techniques like crystallography, NMR spectroscopy etc. Computation based techniques estimate the possible base pairs that could be formed in RNA. Soft computing techniques generally select some random pair or pair sequences and then check them according to some parameters. The final sequence of RNA which is closest to the required fitness is selected as t...