Transforming landscapes: Modeling land-use patterns of environmental borderlands

How did socio-cultural transformation processes change land-use patterns? Throughout the last 50 years, outstanding comprehensive geographic, archaeobiological, and archaeological data have been produced for the area of Oldenburger Graben, Schleswig-Holstein, Germany. Based on this exceptional data set, we are able to study the land-use patterns for a period ranging from the Final Mesolithic until the Late Neolithic (4600–1700 BCE). By application of fuzzy modeling techniques, these patterns are investigated diachronically in order to assess the scale of transformations between the different archaeological phases. Based on nutrient requirements and proposed dietary composition estimates derived from empirical archaeobotanical, archaeozoological, and stable isotope data, the required extent of the areas for different land-use practices are modeled. This information is made spatially explicit using a fuzzy model that reconstructs areas of potential vegetation and land-use for each transformation phase. Pollen data are used to validate the type and extent of land-use categories. The model results are used to test hypotheses on the dynamics of socio-cultural transformations: can we observe a diversification of land-use patterns over time or does continuity of land-use practices prevail? By integrating the different lines of evidence within a spatially explicit modeling approach, we reach a new quality of data analysis with a high degree of contextualization. This allows testing of hypotheses about Neolithic transformation processes by an explicit adjustment of our model assumptions, variables, and parameters

The impact of the fuzzy front end on new product development success in Japanese NPD projects

In a study of Japanese New Product Development (NPD) projects, the fuzzy front end of innovation is explored. Our conceptual model is based on the information-processing perspective. A structual equation model was fitted to data from 497 NPD projects from Japanese mechanical and electrical engineering firms to test the proposed model. The empirical analysis found support for all hypotheses except for one. Our study suggests that an early reduction of market and technical uncertainty and a draft initial planning prior to development have a positive impact on NPD project success. The model accounts for 17% of the variance of the efficiency and 24% of the variance of the effectiveness dependent variable. Thus, the front end phase is an important driver of NPD project success. Implications of the model are discussed. --

A Model for an Intelligent Support Decision System in Aquaculture

The paper purpose an intelligent software system agents–based to support decision in aquculture and the approach of fish diagnosis with informatics methods, techniques and solutions. A major purpose is to develop new methods and techniques for quick fish diagnosis, treatment and prophyilaxis at infectious and parasite-based known disorders, that may occur at fishes raised in high density in intensive raising systems. But, the goal of this paper is to presents a model of an intelligent agents-based diagnosis method will be developed for a support decision system.support decision system, diagnosis, multi-agent system, fish diseases

"Can Banks Learn to Be Rational?"

Can banks learn to be rational in their lending activities? The answer depends on the institutionally bounded constraints to learning. From an evolutionary perspective the functionality (for survival) of "learning to be rational" creates strong incentives for such learning without, however, guaranteeing that each member of the particular economic species actually achieves increased fitness. I investigate this issue for a particular economic species, namely, commrercial banks. The purpose of this paper is to illustrate the key issues related to learning in an economic model by proposing a new screening model for bank commercial loans that uses the neuro fuzzy technique. The technical modeling aspect is integrally connected in a rigorous way to the key conceptual and theoretical aspects of the capabilities for learning to be rational in a broad but precise sense. This paper also compares the relative predictability of loan default among three methods of prediction--- discriminant analysis, logit type regression, and neuro fuzzy--- based on the real data obtained from one of the banks in Taiwan.The neuro fuzzy model, in contrast with the other two, incorporates recursive learning in a real world, imprecise linguistic environment. The empirical results show that in addition to its better screening ability, the neuro fuzzy model is superior in explaining the relationship among the variables as well. With further modifications,this model could be used by bank regulatory agencies for loan examination and by bank loan officers for loan review. The main theoretical conclusion to draw from this demonstration is that non-linear learning in a vague semantic world is both possible and useful. Therefore the search for alternatives to the full neoclassical rationality and its equivalent under uncertainty---rational expectations--- is a plausible and desirable search, especially when the probability for convergence to a rational expectations equilibrium is low.

A Manifesto for the Equifinality Thesis.

This essay discusses some of the issues involved in the identification and predictions of hydrological models given some calibration data. The reasons for the incompleteness of traditional calibration methods are discussed. The argument is made that the potential for multiple acceptable models as representations of hydrological and other environmental systems (the equifinality thesis) should be given more serious consideration than hitherto. It proposes some techniques for an extended GLUE methodology to make it more rigorous and outlines some of the research issues still to be resolved