Word segmentation for a Chinese sentence is essential for many applications in language and speech processing. There’s no perfect method that could achieve word segmentation without any errors. We propose a confidence measure for the segmentation result to cope with the problem caused by the errors. The effective method depends mainly on the error analysis of the word segmentation. With the con...

this paper submitting the computation of optimize point of ordering in inventory control systems and particularly for continuous review of ordering system (r,q) by fuzzy logic method which similarly can be used for other ordering systems. since in the ordering models we cannot forecast the parameters like cost exactly, we have ambiguity. in this case using precise parameters may cause wrong dec...

OBJECTIVE We examine the effects of two different kinds of decision-aiding automation errors on human-automation interaction (HAI), occurring at the first failure following repeated exposure to correctly functioning automation. The two errors are incorrect advice, triggering the automation bias, and missing advice, reflecting complacency. BACKGROUND Contrasts between analogous automation erro...

I apply some of the lessons from quantum theory, in particular from Bell’s theorem, to a debate on the foundations of decision theory and causation. By tracing a formal analogy between the basic assumptions of Causal Decision Theory (CDT)—which was developed partly in response to Newcomb’s problem— and those of a Local Hidden Variable (LHV) theory in the context of quantum mechanics, I show tha...

Jones and Dzhafarov (2014) provided a useful service in pointing out that some assumptions of modern decision-making models require additional scrutiny. Their main result, however, is not surprising: If an infinitely complex model was created by assigning its parameters arbitrarily flexible distributions, this new model would be able to fit any observed data perfectly. Such a hypothetical model...

Abstract Optimism about our ability to enhance societal decision‐making by leaning on Machine Learning (ML) for cheap, accurate predictions has palled in recent years, as these ‘cheap’ have come at significant social cost, contributing systematic harms suffered already disadvantaged populations. But what precisely goes wrong when ML wrong? We argue that, well more obvious concerns the downstrea...

In this work, probability equations are derived for the five node networks and the probabilities are computed for unnecessary handover, missing handover and wrong decisions. Wrong decision probability is the summation of unnecessary and missing handover probabilities. Also, the handover probability is computed for the bandwidths up to 20. The modeling is based on the five state Morkov chain mod...

In the current age of big data, decision trees are one of the most commonly applied data mining methods. However, for reliable results they require up-to-date input data, which is not always given in reality. We present a two-phase approach based on probability theory for considering currency of stored data in decision trees. Our approach is efficient and thus suitable for big data applications...

Michael Schmuker " All models are wrong, but some models are useful. " – George E. P. Box (1979)

The role of management is very important in the strategic growth and development any organization long run. Important decision making a critical factor for planning organizational vision mission. There are times when this needs to be relooked from fresh pair eyes apply learning past experience reset it suit current requirements. This paper talks about analysis resetting organization. Secondary ...