a wireless sensor network consists of many inexpensive sensor nodes that can be used toconfidently extract data from the environment .nodes are organized into clusters and in each cluster all non-cluster nodes transmit their data only to the cluster-head .the cluster-head transmits all received data to the base station .because of energy limitation in sensor nodes and energy reduction in each d...

We introduce an algorithm that solves the maximum ow problem without generating ows explicitly The algorithm solves di rectly a problem we call the maximum s excess problem That problem is equivalent to the minimum cut problem and is a direct extension of the maximum closure problem The concepts used also lead to a new parametric analysis algorithm generating all breakpoints in the amount of ti...

In order to improve the cooperative operation scheduling effect of agricultural machinery, this article uses particle swarm neural network study algorithm machinery and improves intelligent machinery. Aiming at mixed integer nonlinear programming problem, proposes a collaborative population intelligence linear programming. The outer layer improved IPSO module, inner simplex SIM optimal solution...

Akgiil, M., A genuinely polynomial primal simplex algorithm for the assignment problem, Discrete Applied Mathematics 45 (1993) 93-l 15. We present a primal simplex algorithm that solves the assignment problem in :n(n+3)-4 pivots. Starting with a problem of size 1, we sequentially solve problems of size 2,3,4,. ..,lt. The algorithm utilizes degeneracy by working with strongly feasible trees and ...

Developing a polynomial time algorithm for the minimum cost flow problem has been a long standing open problem. In this paper, we develop one such algorithm that runs in O(min(n 2m log nC, n2m 2 log n)) time, where n is the number of nodes in the network, m is the number of arcs, and C denotes the maximum absolute arc costs if arc costs are integer and 0 otherwise. We first introduce a pseudopo...

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...

the aim of this study was to estimate suspended sediment by the ann model, dt with cart algorithm and different types of src, in ten stations from the lorestan province of iran. the results showed that the accuracy of ann with levenberg-marquardt back propagation algorithm is more than the two other models, especially in high discharges. comparison of different intervals in models showed that r...

DYLP is a full implementation of the dynamic simplex algorithm for linear programming. Dynamic simplex attempts to maintain a reduced active constraint system by regularly purging loose constraints and variables with unfavourable reduced costs, and adding violated constraints and variables with favourable reduced costs. In abstract, the code alternates between primal and dual simplex algorithms...

For the problem of cloud service selection, this paper gives a hybrid algorithm. The hybrid algorithm is composed mainly by Simplex Method and Genetic Algorithm. In this algorithm, a tree traversal sequence encoding scheme and some Simplex Method operations are proposed. The design of the tree traversal sequence encoding can support various types of service combinations. In addition, the hybrid...