Fuzzy Classifiers are an powerful class of fuzzy systems. Evolving fuzzy classifiers from numerical data has assumed lot of remarks in the recent past. This paper proposes a method of evolving fuzzy classifiers using a three step technique. In the first step, a modified Fuzzy C–Means Clustering technique is applied to generate membership functions. In the next step, rule base are generated usin...

Aiming to effectively recognize train center plate bolt loss faults, this paper presents an improved fault detection method. A multi-scale local binary pattern operator containing the local texture information of different radii is designed to extract more efficient discrimination information. An improved teaching-learning-based optimization algorithm is established to optimize the classificati...

Scheduling concerns the allocation of limited resources overtime to perform tasks fulfill certain criterion and optimize one or several objective functions. One most popular models in scheduling theory is that flow-shop scheduling. During last 40 years, permutation sequencing problem with makespan minimization has held attraction many researchers. This characterized as Fm/prmu/Cmax notation Gra...

Abstract For the low-voltage transformer district with distributed generations (DGs), traditional theoretical calculation method of line loss is not applicable. This paper presents a novel clustering for data DGs, which combined an improved Cuckoo Search algorithm and K-Means algorithm. Firstly, influence factors are screened based on maximum information coefficient, index system established. S...

Cuckoo Search (CS) algorithm is a nature-inspired optimization (NIOA) with less control parameters that stable, versatile, and easy to implement. CS has good global search capabilities, but it prone local optima problems. As result, may be possible improve the classic algorithm's capability. Centered on fuzzy set theory, this paper introduces an improved version. The population of solutions bee...

Cuckoo search (CS) is an efficient swarm-intelligence-based algorithm and significant developments have been made since its introduction in 2009. CS has many advantages due to its simplicity and efficiency in solving highly non-linear optimisation problems with real-world engineering applications. This paper provides a timely review of all the state-of-the-art developments in the last five year...

In this paper, the metaheuristics algorithm Cuckoo Search (CS), is adapted and applied for a model parameter identification of an E. coli fed-batch cultivation process. The dynamics of bacteria growth and substrate (glucose) utilization is described by a system of ordinary nonlinear differential equations. Using real experimental data set from an E. coli MC4110 fed-batch cultivation process a p...