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...

In this paper a new efficient approach to solving the balanced connected partitioning is presented. The graph partitioning problem has been used in many areas of computer science like LSI design; electrical power networks (EPNs) and ect. The problem aims to obtaining sub graphs of a graph which include balance connected vertices. The proposed solution is based on Cuckoo Optimization Algorithm (...

This paper presents a Cuckoo Optimization Algorithm (COA) model for the cost optimization of the one-way and two-way reinforced concrete (RC) slabs according to ACI code. The objective function is the total cost of the slabs including the cost of the concrete and that of the reinforcing steel. In this paper, One-way and two-way slabs with various end conditions are formulated as ACI code. The t...

Cuckoo Search is gaining a lot of attention as a new soft computing technique inspired by nature,in this research the application of Cuckoo Search for solving the problem of estimating the parameters of a nonlinear model is investigated from both aspects of efficiency and robustness. Using a case study of estimation of parameters of a nonlinear model for the cutting tool temperature in an indus...

In this paper, Hybridization of Cuckoo Search algorithm with Powell Search (HCSPS) is used to solve optimal reactive power problem. Cuckoo search (CS) has been recently projected as a population-based optimization algorithm and it is has so far been efficaciously applied in a variety of fields. The inertia weight of Levy flights is presented to balance the capability of global and local search....

neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...

Cuckoo search (CS) was introduced in 2009, and it has attracted great attention due to its promising efficiency in solving many optimization problems and real-world applications. In the last few years, many papers have been published regarding cuckoo search, and the relevant literature has expanded significantly. This chapter summarizes briefly the majority of the literature about cuckoo search...

Today, the information is growing enormously and it is difficult and tedious task to retrieve the necessary information from that pool. The main area for retrieving relevant answers is called intelligent information retrieval. To achieve this, question and answering system is used. This question and answering plays a major role in user query processing, information retrieval and extracting rela...

Constrained Nonlinear programming problems are hard problems, and one of the most widely used and common problems for production planning problem to optimize. In this study, one of the mathematical models of production planning is survey and the problem solved by cuckoo algorithm. Cuckoo Algorithm is efficient method to solve continues non linear problem. Moreover, mentioned models of productio...

In this paper, a comparative study is carried using three nature-inspired algorithms namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Cuckoo Search (CS) on clustering problem. Cuckoo search is used with levy flight. The heavy-tail property of levy flight is exploited here. These algorithms are used on three standard benchmark datasets and one real-time multi-spectral satelli...