"Comment on 'Articulation of values'": Response to Cochran (1988).

We respond to Cochran's critique of our 1986 study, which was in part a replication of Cochran's original grid methodology for the study of career values. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

模式识别催化剂生产调优

本文介绍如何将模式识别应用于生产调优,着重讨论了多指标(优化目标)因素的分级,提出了用模糊综合评价度量和依有序聚类最小损失函数准则划类,并相继进行变量与样本筛选、信息压缩、特征提取和模拟仿真获得优区操作条件,实施效果显著。     

Fixed point theorems on fuzzy normed linear spaces

In this paper, definitions of strongly fuzzy convergent sequence, l-fuzzy weakly convergent sequence and l-fuzzy weakly compact set are given in a fuzzy normed linear space. The concepts of fuzzy normal structure, fuzzy non-expansive mapping, uniformly convex fuzzy normed linear space are introduced and fixed point theorems for fuzzy non-expansive mappings are proved.     

Using memory and fuzzy rules in a co-operative multi-thread strategy for optimization

In this article, we analyze a co-operative multi-thread search-based optimization strategy, where each solver thread represents a different optimization algorithm (or the same one with different settings), and they are all controlled by a centralized co-ordinator. We also propose the use of memory to keep track of both the state of the individual threads and the obtained solutions. Based on this memory, a very simple fuzzy rule base is used to control the system behavior.We also present the results of three computational experiments. The first of these checks the strategy by comparing it with an independent search strategy and a sequential algorithm, and the superiority of the co-operative scheme is confirmed. The second analyzes how definition of the threads affects the quality of the results, and the importance of there being a balanced set between intensification and diversification is corroborated. The third explores the use of memory with two different fuzzy rules, and the results indicate that the best combination is to use memory together with two rules (solver dependent and solver independent ones) (although this combination should not be activated at the beginning of the search in order to avoid premature convergence).     

A general class of simple majority decision rules based on linguistic opinions

In this paper we have introduced a class of decision rules related to simple majority, by considering individual intensities of preference. These intensities will be shown by means of linguistic labels. In order to compare the amount of opinion obtained by each alternative, we have considered the total ordered monoid generated by the sums of the original labels, according to an addition and an ordering. In this general framework different sets of linguistic labels can be employed and these sets can be represented by means of diverse mathematical objects. Moreover, on these mathematical representations of linguistic labels several orderings can be considered. Thus, flexibility is an important feature of this new class of group decision making procedures. Some examples of putting in practice the simple majority decision rules based on linguistic labels are provided, and the main properties of these voting systems are analyzed. It is worth emphasizing that these properties are satisfied for any total ordered monoid, regardless of the mathematical representation of linguistic labels or the ordering used to compare collective opinions.     

Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons

In this paper, we propose and investigate a new category of neurofuzzy networks—fuzzy polynomial neural networks (FPNN) endowed with fuzzy set-based polynomial neurons (FSPNs) We develop a comprehensive design methodology involving mechanisms of genetic optimization, and genetic algorithms (GAs) in particular. The conventional FPNNs developed so far are based on the mechanisms of self-organization, fuzzy neurocomputing, and evolutionary optimization. The design of the network exploits the FSPNs as well as the extended group method of data handling (GMDH). Let us stress that in the previous development strategies some essential parameters of the networks (such as the number of input variables, the order of the polynomial, the number of membership functions, and a collection of the specific subset of input variables) being available within the network are provided by the designer in advance and kept fixed throughout the overall development process. This restriction may hamper a possibility of developing an optimal architecture of the model. The design proposed in this study addresses this issue. The augmented and genetically developed FPNN (gFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNNs. The GA-based design procedure being applied at each layer of the FPNN leads to the selection of the most suitable nodes (or FSPNs) available within the FPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gFPNN is quantified through experimentation in which we use a number of modeling benchmarks—synthetic and experimental data being commonly used in fuzzy or neurofuzzy modeling. The obtained results demonstrate the superiority of the proposed networks over the models existing in the references.     

Understanding source effects in ADHD rating scales: Reply to DuPaul (2003).

G. J. DuPaul (see record 2003-02033-012) offered two suggestions for additional research to understand the strong source effects reported by R. Gomez, G. L Burns, J. A. Walsh, and M. A. de Moura (see record 2003-02033-001) in attention-deficit/ hyperactivity disorder (ADHD) rating scales. The first suggestion was to determine whether the source effects represent mostly bias or accuracy. The second suggestion was to minimize source effects through the development of better ADHD rating scales. Because source effects can represent bias or accuracy, it is important to minimize the bias aspect through content validation procedures prior to attempts to determine whether source effects better reflect bias or accuracy. This comment offers various suggestions to reduce the bias in ADHD rating scales. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于模糊神经网络对经济的聚类分析

在现实生活中具有同等人力资本的劳动者在不同的生产力环境下的经济贡献率是不同的 ,有时甚至不可比较的。利用人工神经网络 (SOM网络 ) ,通过 Matlab语言编程 ,根据技术进步增长率对整个经济进行模式分类。分类的结果是大致把 2 9个省市分为 6个类 ,反映了各地区的经济与技术进步增长率情况     

Multidimensional Personality Questionnaire profiles of veterans with traumatic combat exposure: Externalizing and internalizing subtypes.

This study used the Multidimensional Personality Questionnaire (MPQ; A. Tellegen, in press) to identify personality-based subtypes of posttraumatic response. Cluster analyses of MPQs completed by combat veterans revealed subgroups that differed on measures relating to the externalization versus internalization of distress. The MPQ profile of the externalizing cluster was defined by low Constraint and Harmavoidance coupled with high Alienation and Aggression. Individuals in this cluster also had histories of delinquency and high rates of substance-related disorder. In comparison, the MPQ profile of the internalizing cluster was characterized by lower Positive Emotionality, Alienation, and Aggression and higher Constraint, and individuals in this cluster showed high rates of depressive disorder. These findings suggest that dispositions toward externalizing versus internalizing psychopathology may account for heterogeneity in the expression of posttraumatic responses, including patterns of comorbidity. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Broad View of Intelligence: The Theory of Successful Intelligence.

This article reviews the theory of successful intelligence and attempts to construct-validate the theory of successful intelligence. It describes 4 distinct converging operations that have been used in these attempts. Two sets involve internal validation of the structure of the theory and 2 sets external validation of the theory with outside criteria. The internal validation operations involve information-processing (componential) analyses and both exploratory and confirmatory factor analyses. The external validation operations involve correlational analysis and analyses of instructional interventions based on the theory. The results are generally supportive of the theory and suggest that conventional conceptions of intelligence may be too narrow. The theory is of use in consulting because it broadens the scope of skills one looks for in seeking "intelligent" people for hiring, retention, and promotion and in assessing a person's ability to do his or her current job. (PsycINFO Database Record (c) 2010 APA, all rights reserved)