Multi-hazard analysis and identification of priority settlements for land management in Haiti

Seismic hazard study in “La Hispaniola” island in connection with the land tenure situation in the region, in order to define priority areas with a high risk, where some land management recommendations are proposed. The seismic hazard assessment has been carried out following the probabilistic method with a seismogenic zonation and including the major faults of the region as independent units. In order to identify the priority areas, it has taken into account, besides the seismic hazard study, the map of changes of static Coulomb failure stress and the landslide hazard map.

A fuzzy MCDA framework for safety assessment in the remediation of a uranium mill tailings site in Ukraine

The Pridneprovsky Chemical Plant was one of the largest uranium processing enterprises in the former USSR, producing a huge amount of uranium residues. The Zapadnoe tailings site contains most of these residues. We propose a theoretical framework based on multicriteria decision analysis and fuzzy logic to analyze different remediation alternatives for the Zapadnoe tailings, which simultaneously accounts for potentially conflicting economic, social and environmental objectives. We build an objective hierarchy that includes all the relevant aspects. Fuzzy rather than precise values are proposed for use to evaluate remediation alternatives against the different criteria and to quantify preferences, such as the weights representing the relative importance of criteria identified in the objective hierarchy. Finally, we suggest that remediation alternatives should be evaluated by means of a fuzzy additive multi-attribute utility function and ranked on the basis of the respective trapezoidal fuzzy number representing their overall utility.

Fuzzy MCDA for remediation of a uranium tailing

The Pridneprovsky Chemical Plant was a largest uranium processing enterprises, producing a huge amount of uranium residues. The Zapadnoe tailings site contains the majority of these residues. We propose a theoretical framework based on Multi-Criteria Decision Analysis and fuzzy logic to analyse different remediation alternatives for the Zapadnoe tailings, in which potentially conflicting economic, radiological, social and environmental objectives are simultaneously taken into account. An objective hierarchy is built that includes all the relevant aspects. Fuzzy rather than precise values are proposed for use to evaluate remediation alternatives against the different criteria and to quantify preferences, such as the weights representing the relative importance of criteria identified in the objective hierarchy. Finally, it is proposed that remediation alternatives should be evaluated by means of a fuzzy additive multi-attribute utility function and ranked on the basis of the respective trapezoidal fuzzy number representing their overall utility.

Modelo preditivo fuzzy da mobilização do solo no sistema de plantio direto.

As culturas do milho e da soja respondem pela maior parte da produção nacional de grãos, predominando o sistema de plantio direto. Para uma semeadura direta de qualidade, o bom aterramento do sulco é indispensável, pois garante um ambiente adequado às sementes. Neste sentido, é importante estimar a mobilização de solo promovida por uma haste sulcadora estreita durante esta operação. O modelo analítico existente visa representar a mobilização do solo no sistema de plantio convencional. Como consequência, há situações em que este não pode se aplicado, como no caso de hastes sulcadoras estreitas utilizadas em semeadoras de plantio direto. Nestas situações, o mecanismo de falha do solo pode se alterar, assumindo um comportamento não modelado na literatura. Essa pesquisa propõe um modelo fuzzy capaz de representar estas situações, aproveitando conhecimento da teoria de mecânica dos solos e da análise de resultados experimentais. No modelo proposto, parte das regras descrevem situações não abrangidas pelo modelo analítico, as quais foram formuladas a partir da estimativa das prováveis áreas de solo mobilizado. O modelo fuzzy foi testado com dados de experimentos conduzidos durante a pesquisa, em duas condições de granulometria de solo (arenoso e argiloso). O modelo proposto reproduziu as tendências observadas nos dados experimentais, mas superestimou os valores de área observados, sendo esse efeito bem mais intenso para os dados do experimento em solo arenoso. A superestimativa ocorreu devido à soma de diversos fatores. Um deles é a diferença entre as leituras experimentais, as quais consideram apenas o solo realmente movimentado, e a premissa do modelo analítico, que considera toda a área de solo incluindo aquela cisalhada, porém não mobilizada. Outro fator foi devido ao efeito do disco de corte da palha, que pré-cisalha o solo à frente da ferramenta. No ensaio em solo arenoso os valores observados de área de solo mobilizado foram menores que os esperados, intensificando o efeito de superestimativa do modelo fuzzy, sendo que este efeito não representa uma deficiência deste modelo.

Fuzzy control of a water pump for an agricultural plant growth system

At the present time there is a high pressure toward the improvement of all the production processes. Those improvements can be sensed in several directions in particular those that involve energy efficiency. The definition of tight energy efficiency improvement policies is transversal to several operational areas ranging from industry to public services. As can be expected, agricultural processes are not immune to this tendency. This statement takes more severe contours when dealing with indoor productions where it is required to artificially control the climate inside the building or a partial growing zone. Regarding the latter, this paper presents an innovative system that improves energy efficiency of a trees growing platform. This new system requires the control of both a water pump and a gas heating system based on information provided by an array of sensors. In order to do this, a multi-input, multi-output regulator was implemented by means of a Fuzzy logic control strategy. Presented results show that it is possible to simultaneously keep track of the desired growing temperature set-point while maintaining actuators stress within an acceptable range.

Controlo fuzzy semi-activo para aparelhos de amortecimento variável na protecção sísmica

Trabalho apresentado no 10º Congresso Nacional de Sismologia e Engenharia Sísmica, 20-22 abril de 2016, Ponta Delgada, Açores, Portugal

Vasa Creek Channel Conditions and Slope Stability, Bellevue, Washington

The focus of this report is is the channel conditions at Vasa Creek, Bellevue, Washington, with regard to kokanee habitat and slope stability. This required a geomorphic and geologic assessment of the stream and riparian corridor along Vasa Creek. I focused my efforts in a 720m study-reach just south of I-90 in which City of Bellevue had no information. My assessment is divided into 3 categories: channel morphology, geology, and landslide hazards. I described the channel morphology by determining the gradient of the channel, longitudinal and cross-channel geometries, grain size distribution, embeddedness observations, type of channel reaches present, and the locations of significant in-channel woody-debris, landslides, scarps, landslide debris, and erosional features. This was done by conducting a longitudinal survey, 7 cross-channel surveys, pebble counts, and visual observations with the aid of a GPS device for mapping. I completed my geological assessment using both field observations and borehole data provided by GeoMapNW. Borehole data provided logs of the subsurface material at specific locations. In the field, I interpreted local geology using material in the channel as well as exposures in the adjacent slope. I completed the landslide hazard assessment using GIS methods supplemented by field observations. GIS methods included the use of aerial LiDAR to discern slope values and locations of features. Features of interest include the locations of scarps, landslides, landslide debris, and erosional features which were observed in the field. I classified 4 slope classes using ArcMap10 along with the locations of previously mapped landslides, scarps, and landslide debris. I describe the risk of slope failure according to the Washington Administration Code definition of critical areas (WAC 365-190-120 6a-i). My results are presented in the form of a map suite containing a channel morphology map, geology map, and landslide hazard map. The channel is a free-formed alluvial plane-bed reach with infrequent step-pools with riffles associated with landslide debris that chokes the channel. Overall I found that there is not the potential for kokanee habitat due flashy behavior (sudden high flow events), landslide inundation, and a lack of favorable conditions within the channel. The updated geologic map displays advance outwash deposits and alluvium present within the study-reach, as opposed to exposures of the Blakeley Formation along with other corrections from borehole data interpretations. The landslide hazard map shows that there are areas at high risk for slope failure along the channel that should be looked into further.

Off-line signature verification and forgery detection using fuzzy modeling

Automatic signature verification is a well-established and an active area of research with numerous applications such as bank check verification, ATM access, etc. This paper proposes a novel approach to the problem of automatic off-line signature verification and forgery detection. The proposed approach is based on fuzzy modeling that employs the Takagi-Sugeno (TS) model. Signature verification and forgery detection are carried out using angle features extracted from box approach. Each feature corresponds to a fuzzy set. The features are fuzzified by an exponential membership function involved in the TS model, which is modified to include structural parameters. The structural parameters are devised to take account of possible variations due to handwriting styles and to reflect moods. The membership functions constitute weights in the TS model. The optimization of the output of the TS model with respect to the structural parameters yields the solution for the parameters. We have also derived two TS models by considering a rule for each input feature in the first formulation (Multiple rules) and by considering a single rule for all input features in the second formulation. In this work, we have found that TS model with multiple rules is better than TS model with single rule for detecting three types of forgeries; random, skilled and unskilled from a large database of sample signatures in addition to verifying genuine signatures. We have also devised three approaches, viz., an innovative approach and two intuitive approaches using the TS model with multiple rules for improved performance. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

A soft-computing-based method for the automatic discovery of fuzzy rules in databases:uses for academic research and management support in marketing

The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method. © 2012 Published by Elsevier Inc.

Performance measurement with fuzzy data envelopment analysis

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

Intonation contour realisation for Standard Yorùbá text-to-speech synthesis:a fuzzy computational approach

This paper presents a novel intonation modelling approach and demonstrates its applicability using the Standard Yorùbá language. Our approach is motivated by the theory that abstract and realised forms of intonation and other dimensions of prosody should be modelled within a modular and unified framework. In our model, this framework is implemented using the Relational Tree (R-Tree) technique. The R-Tree is a sophisticated data structure for representing a multi-dimensional waveform in the form of a tree. Our R-Tree for an utterance is generated in two steps. First, the abstract structure of the waveform, called the Skeletal Tree (S-Tree), is generated using tone phonological rules for the target language. Second, the numerical values of the perceptually significant peaks and valleys on the S-Tree are computed using a fuzzy logic based model. The resulting points are then joined by applying interpolation techniques. The actual intonation contour is synthesised by Pitch Synchronous Overlap Technique (PSOLA) using the Praat software. We performed both quantitative and qualitative evaluations of our model. The preliminary results suggest that, although the model does not predict the numerical speech data as accurately as contemporary data-driven approaches, it produces synthetic speech with comparable intelligibility and naturalness. Furthermore, our model is easy to implement, interpret and adapt to other tone languages.

Unsupervised KDD to creatively support managers' decision making with fuzzy association rules:a distribution channel application

To be competitive in contemporary turbulent environments, firms must be capable of processing huge amounts of information, and effectively convert it into actionable knowledge. This is particularly the case in the marketing context, where problems are also usually highly complex, unstructured and ill-defined. In recent years, the development of marketing management support systems has paralleled this evolution in informational problems faced by managers, leading to a growth in the study (and use) of artificial intelligence and soft computing methodologies. Here, we present and implement a novel intelligent system that incorporates fuzzy logic and genetic algorithms to operate in an unsupervised manner. This approach allows the discovery of interesting association rules, which can be linguistically interpreted, in large scale databases (KDD or Knowledge Discovery in Databases.) We then demonstrate its application to a distribution channel problem. It is shown how the proposed system is able to return a number of novel and potentially-interesting associations among variables. Thus, it is argued that our method has significant potential to improve the analysis of marketing and business databases in practice, especially in non-programmed decisional scenarios, as well as to assist scholarly researchers in their exploratory analysis. © 2013 Elsevier Inc.

The Fuzzy-Neuro Classifier for Decision Support

This paper aims at development of procedures and algorithms for application of artificial intelligence tools to acquire process and analyze various types of knowledge. The proposed environment integrates techniques of knowledge and decision process modeling such as neural networks and fuzzy logic-based reasoning methods. The problem of an identification of complex processes with the use of neuro-fuzzy systems is solved. The proposed classifier has been successfully applied for building one decision support systems for solving managerial problem.

A Geometrical Interpretation to Define Contradiction Degrees between Two Fuzzy Sets

For inference purposes in both classical and fuzzy logic, neither the information itself should be contradictory, nor should any of the items of available information contradict each other. In order to avoid these troubles in fuzzy logic, a study about contradiction was initiated by Trillas et al. in [5] and [6]. They introduced the concepts of both self-contradictory fuzzy set and contradiction between two fuzzy sets. Moreover, the need to study not only contradiction but also the degree of such contradiction is pointed out in [1] and [2], suggesting some measures for this purpose. Nevertheless, contradiction could have been measured in some other way. This paper focuses on the study of contradiction between two fuzzy sets dealing with the problem from a geometrical point of view that allow us to find out new ways to measure the contradiction degree. To do this, the two fuzzy sets are interpreted as a subset of the unit square, and the so called contradiction region is determined. Specially we tackle the case in which both sets represent a curve in [0,1]2. This new geometrical approach allows us to obtain different functions to measure contradiction throughout distances. Moreover, some properties of these contradiction measure functions are established and, in some particular case, the relations among these different functions are obtained.