Technology centered organizations must be able to identify promising new products or process improvements at an early stage so that the necessary resources can be allocated to those activities. It is essential to invest in targeted research and development (R and D) projects as opposed to a wide range of ideas so that resources can be focused on successful outcomes. The selection of the most ap...

Variable (feature) selection has attracted much attention in contemporary statistical learning and recent scientific research. This is mainly due to the rapid advancement in modern technology that allows scientists to collect data of unprecedented size and complexity. One type of statistical problem in such applications is concerned with modeling an output variable as a function of a sma...

The soundness and efficiency of banks is one of the important subjects that neglecting it can have adverse consequences for every country's economy. For economies depending on the money market, such as the Iran economy, this subject is more critical. Therefore, in this study, using panel data related to 16 Iranian banks for the annual period of 2010-2017, the economic efficiency was determined ...

Due to the importance of supplier selection issue in supply chain management (SCM) and ,also,  the increasing tendency of organizations to their social responsibilities, In this paper, we survey the supplier selection issue as a multi objective problem while considering the factor of corporate social responsibility (CSR) as a mathematical parameter. The purpose of this paper is to design a mode...

Direct weak or strong measurement of quantum wave function has been demonstrated based on the post-selection; however, efficiency is greatly limited by success probability post-selection. Here we propose a modified scheme to directly measure photon's simply inserting liquid crystal plate after coupling between pointer and function. Our method can significantly increase post selection. Numerical...

this paper defines how a meta heuristic search engine called p.s.o can be used to maximize the objective function of a logistic regression model, describing the relationship between the response variable (product designs' score) and a set of explanatory variables (product design factors). at the first phase the processed data, classified and categorized, by kansie engineering is used as input t...

Inspired by the success of the Lasso for regression analysis (Tibshirani, 1996), it seems attractive to estimate the graph of a multivariate normal distribution by `1-norm penalised likelihood maximisation. The objective function is convex and the graph estimator can thus be computed efficiently, even for very large graphs. However, we show in this note that the resulting estimator is not consi...

Most reinforcement learning algorithms rely on the use of some function approximation method. In general, their performance will be largely influenced by what function approximation method is used and how it is configured. Current practice is that the user of the algorithm decides about both the method and its configuration, such as the number and nature of basis functions for a linear function...

The choice of suitable robots in manufacturing, to improve product quality and to increase productivity, is a complicated decision due to the increase in robot manufacturers and configurations. In this article, a novel approach is proposed to choose among alternatives, differently assessed by decision makers on different criteria, to make the final evaluation for decision-making. The approach i...

This paper shows how we can make advantage of using genetic programming in selection of suitable features for automatic modulation recognition. Automatic modulation recognition is one of the essential components of modern receivers. In this regard, selection of suitable features may significantly affect the performance of the process. Simulations were conducted with 5db and 10db SNRs. Test and ...