TOPSIS method for quality credit evaluation: A case of air-conditioning market in China

Quality credit is a new concept invented in China and to the best of our knowledge, there hasn’t been a widely-accepted quality credit indicator system and no quantitative method has been employed in quality credit evaluation up to now. To take the researches on quality credit a step further, this paper aims to establish a quality credit evaluation indicator system for air-conditioning enterprises in Chinese market and use TOPSIS (technique for order preference by similarity to ideal solution) method to evaluate quality credit of the enterprises. Based on the data of 8 air-conditioning enterprises, including 6 Chinese enterprises and 2 Japanese enterprises, three experiments with three different indicator systems are used to determine the final indicator system and verify the feasibility and effectiveness of TOPSIS. In Experiment one, an original indicator system is established to evaluate the quality credit of the 8 enterprises. In Experiment two and three, two reasonably adjusted indicator systems are used and the indicator system in Experiment three is the final one that we recommend. The analysis of experiments verifies that the proposed quality credit indicator system is reliable and TOPSIS is suitable for quality credit evaluation.     

A fuzzy interpretation for an ecological site classification case

A case study is presented in which four sites in the Jebel Marra highlands in western Sudan and four sites from the Erkowit plateau in eastern Sudan are classified according to a list of collected soil fauna taxa and their densities. The fuzzy isodata algorithm was used satisfactorily to classify the sites in accordance with a biologist's observations. Comparison of the fuzzy classification with the results of some ordination methods is also given.     

The initiation,evaluation and selection of operational research projects

This paper discusses the problems involved in conducting successful Operational Research within a large organisation and suggests ways of overcoming them. It describes ways in which Operational Research projects arise, methods of assessing their relative merits, and methods used by the authors to obtain a suitable portfolio of projects. It is argued that an Operational Research Group should apply to its own project planning the scientific approach that it advocates for others.     

A case for combinatorics: A research commentary

In this commentary, we make a case for the explicit inclusion of combinatorial topics in mathematics curricula, where it is currently essentially absent. We suggest ways in which researchers might inform the field’s understanding of combinatorics and its potential role in curricula. We reflect on five decades of research that has been conducted since a call by Kapur (1970) for a greater focus on combinatorics in mathematics education. Specifically, we discuss the following five assertions: 1) Combinatorics is accessible, 2) Combinatorics problems provide opportunities for rich mathematical thinking, 3) Combinatorics fosters desirable mathematical practices, 4) Combinatorics can contribute positively to issues of equity in mathematics education, and 5) Combinatorics is a natural domain in which to examine and develop computational thinking and activity. Ultimately, we make a case for the valuable and unique ways in which combinatorics might effectively be leveraged within K-16 curricula.     

Representation of decision making processes in an ecological evaluation system

This paper deals with the problems of knowledge representation for a decision support system (DSS) applicable in a dynamic environment. Some special principles concerning environment applications are considered in order to understand better human decision making and behavior. The approach of representing static and dynamic aspects of a system and reflecting them using deep knowledge representation is proposed. The formalization of multiple objective decision making mechanisms is considered. The results of modeling cognitive processes leading to decisions are demonstrated by an example developed during the design stages of an ecological evaluation system.     

Scarcity of exergy and ecological evaluation based on embodied exergy

The driving force of the earth system is shown to be the cosmic exergy due to radiational difference between the sun and the cosmic background, instead of the solar energy. The scarcity of cosmic exergy availability as the fundamental natural resource for the ecosphere and the human society is revealed by a systematic study on the global consumption of the cosmic exergy in the earth and a budget of the exergy consumption with respect to main terrestrial processes. A conceptual framework or ecological evaluation is developed on the basis of a new concept referred to as embodied exergy in terms of the cosmic exergy consumed directly or indirectly in making or sustaining a general commodity as a product, service or an emission. As a generalization of Szargut’s cumulative exergy consumption in resource analysis, embodied exergy is chosen, in place of embodied energy, to define Odum’s emergy. Concrete calculation schemes for embodied exergy accounting are provided as a systematic revision and rephrasing of existing embodied emergy analysis.     

关于证券投资基金业绩评价方法及其应的探讨

本文从多个角度介绍了证券投资基金评价的各种方法,并结合我国实际情况,对各种方法的优点与不足进行了分析,为投资者评价基金及做出投资选择提供了有效方法。     

The security number of lexicographic products

A subset S of vertices of a graph G is a secure set if |N [X] ∩ S| ≥ |N [X] ? S| holds for any subset X of S, where N [X] denotes the closed neighborhood of X. The minimum cardinality s(G) of a secure set in G is called the security number of G. We investigate the security number of lexicographic product graphs by defining a new concept of tightly-securable graphs. In particular we derive several exact results for different families of graphs which yield some general results.     

The model of security market when the security price is a continuous semimartingale

In this paper, we set the stock price model in security market when the price process is a continuous semartingale, and find a unigue solution of price process model.     

Exploring the use of narrative analysis as an operational research method: A case study in voluntary sector evaluation

Operational research frequently has to deal with situations where the perceptions and views of the various stakeholders involved may be quite different. One such situation is provided by the case of the evaluation of the work of voluntary sector groups, where concepts such as quality are frequently held to be the desired objectives whose achievement should be evaluated, yet where quite different perceptions of these concepts are held by the various parties to the evaluation. Through the use of a case study, this paper illustrates how approaches to narrative analysis like actant analysis and deconstruction can be used alongside other soft OR methods to enable negotiation of common understandings of important concepts like quality.     

A case for a research based methodology in OR problem solving

Many Operational Research techniques assume the existence of sound data, whilst projects are often carried out using, perforce, limited or unreliable data. It is contended that even in such adverse circumstances good, stable solutions can often be found by researching the structure of the problem to be solved, using such data as are available. The contention is illustrated by examples drawn from the authors' experience.     

Volatility forecasting for interbank offered rate using grey extreme learning machine: The case of China

Interbank Offered rate is the only direct market rate in China’s currency market. Volatility forecasting of China Interbank Offered Rate (IBOR) has a very important theoretical and practical significance for financial asset pricing and financial risk measure or management. However, IBOR is a dynamics and non-steady time series whose developmental changes have stronger random fluctuation, so it is difficult to forecast the volatility of IBOR. This paper offers a hybrid algorithm using grey model and extreme learning machine (ELM) to forecast volatility of IBOR. The proposed algorithm is composed of three phases. In the first, grey model is used to deal with the original IBOR time series by accumulated generating operation (AGO) and weaken the stochastic volatility in original series. And then, a forecasting model is founded by using ELM to analyze the new IBOR series. Lastly, the predictive value of the original IBOR series can be obtained by inverse accumulated generating operation (IAGO). The new model is applied to forecasting Interbank Offered Rate of China. Compared with the forecasting results of BP and classical ELM, the new model is more efficient to forecasting short- and middle-term volatility of IBOR.     

The case for structured programming

This report is mainly a response to a paper by Henderson and Snowdon, “An Experiment in Structured Programming”. The notions of structured programming, top-down programming, and stepwise refinement are compared, and some careful guidelines for the proper use of structured programming approaches are suggested.     

The case for strategic oscillation

We study a “hard” optimization problem for metaheuristic search, where a natural neighborhood (that consists of moves for flipping the values of zero-one variables) confronts two local optima, separated by a maximum possible number of moves in the feasible space. Once a descent method reaches the first local optimum, all sequences of feasible moves to reach the second, which is the global optimum, must ultimately pass through solutions that are progressively worse until reaching the worst solution of all, which is adjacent to the global optimum.     

Interpretability-preserving genetic optimization of linguistic terms in fuzzy models for fuzzy ordered classification: An ecological case study

Fuzzy ordered classifiers were used to assign fuzzy labels to river sites expressing their suitability as a habitat for a certain macroinvertebrate taxon, given up to three abiotic properties of the considered river site. The models were built using expert knowledge and evaluated on data collected in the Province of Overijssel in the Netherlands. Apart from a performance measure for crisp classifiers common in the aquatic ecology domain, the percentage of correctly classified instances (% CCI), two performance measures for fuzzy (ordered) classifiers are introduced in this paper: the percentage of correctly fuzzy classified instances (% CFCI) and the average deviation (AD). Furthermore, results of an interpretability-preserving genetic optimization of the linguistic terms, applying once binary encoding and once real encoding, are presented.     

The number of viable ecological trophic networks

The network trophic theory tries to explain the working of basic ecosystems by studying the trophic connections between species. A basic model that helps us to understand some rules that have been followed in the ecosystems is the one known as the model of trophic cascade. By following these ecological criteria, the algorithm that we present allows us to determine the number of viable trophic networks, taking into account the number of trophic levels, the maximum number of species at each level and the links between the different species. A development for five levels is shown.