We may presume the neural networks are simplified models of the biological neurons system. The Artificial Neural Network (ANN) is an information processing system which is inspired by brain learning system. It is assumed that brain is composed of a large number of highly interconnected processing elements working in groups to solve specific problems. Various networks and algorithms have been pr...

Due to the defects caused by limited energy, storage capacity, and computing ability, increasing amount of sensing data has become a challenge in wireless sensor networks (WSNs). To decrease additional power consumption extend lifetime WSN, multistage hierarchical clustering deredundancy algorithm is proposed. In first stage, dual-metric distance employed, redundant nodes are preliminarily iden...

Gündüz Ulusoy Faculty of Engineering and Natural Sciences, Sabancı University, Istanbul, Turkey. [email protected] ABSTRACT This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The objective is to minimize the make-span, i.e. the completion time of all the tasks in the last stage. This problem is of practical interest in the textile and process ...

In this paper, an interior point algorithm for linear programs is adapted for solving multistage stochastic linear programs. The algorithm is based on Monteiro and Adler’s path-following algorithm for deterministic linear programs. In practice, the complexity of the algorithm is linear with respect to the size of the sample space. The algorithm starts from a feasible solution of the problem and...

The widespread use of the object-oriented programs (OOPs) makes the requirement for testsgeneration strategies for testing the OOPs increases from day to day. In this paper, we present a multi-stage genetic algorithm (MSGA) to generate a suite of tests for testing the OOPs. MSGA includes two optimization stages. The first stage concentrates on finding test cases (sequences of called methods), w...

We reexamine the work of Stumm and Walther on multistage algorithms for adjoint computation. We provide an optimal algorithm for this problem when there are two levels of checkpoints, in memory and on disk. Previously, optimal algorithms for adjoint computations were known only for a single level of checkpoints with no writing and reading costs; a well-known example is the binomial checkpointin...

We may presume the neural networks are simplified models of the biological neurons system. The Artificial Neural Network (ANN) is an information processing system which is inspired by brain learning system. It is assumed that brain is composed of a large number of highly interconnected processing elements working in groups to solve specific problems. Various networks and algorithms have been pr...