RNNs have local feedback loops within the network which allows them to shop earlier accessible patterns. This network can be educated with gradient descent back propagation and optimization technique such as second-order methods; conjugate gradient, quasi-Newton, Levenberg-Marquardt have also been used for networks training [14, 15]. But still this algorithm is not definite to find the global m...

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...

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...

Today, in computer science, a computational challenge exists in finding a globally optimized solution from an enormously large search space. Various meta-heuristic methods can be used for finding the solution in a large search space. These methods can be explained as iterative search processes that efficiently perform the exploration and exploitation in the solution space. In this context, thre...

Probabilistic data structures are so popular in membership queries, network applications, and so on. Bloom Filter and Cuckoo Filter are two popular space efficient models that incorporate in set membership checking part of many important protocols. They are compact representation of data that use hash functions to randomize a set of items. Being able to store more elements while keeping a reaso...

In the science of operation research and decision theory, selection is the most important process. Selection is a process that studies multiple qualitative and quantitative criteria, related to the science of management, which are mostly incompatible with each other. The multi criteria selection of a renewable energy portfolio is one of the main issues considered in multi criteria literatur...

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...

Meta-heuristic algorithms are applied in optimization problems in a variety of fields, including engineering, economics, and computer science. In this paper, seven population-based meta-heuristic algorithms are employed for size and geometry optimization of truss structures. These algorithms consist of the Artificial Bee Colony algorithm, Cyclical Parthenogenesis Algorithm, Cuckoo Search algori...

This article considers the parallel machine scheduling problem with step-deteriorating jobs and sequence-dependent setup times. The objective is to minimize the total tardiness by determining the allocation and sequence of jobs on identical parallel machines. In this problem, the processing time of each job is a step function dependent upon its starting time. An individual extended time is pena...