Measuring the Score Matching of the Pairwise Deoxyribonucleic Acid Sequencing using Neuro-Fuzzy

The proposed model for getting the score matching of the deoxyribonucleic acid (DNA) sequence is introduced; the Neuro-Fuzzy procedure is the strategy actualized in this paper; it is used the collection of biological information of the DNA sequence performing with global and local calculations so as to advance the ideal arrangement; we utilize the pairwise DNA sequence alignment to gauge the score of the likeness, which depend on information gathering from the pairwise DNA series to be embedded into the implicit framework; an adaptive neuro-fuzzy inference system model is reasonable for foreseeing the matching score through the preparation and testing in neural system and the induction fuzzy system in fuzzy logic that accomplishes the outcome in elite execution

A new fuzzy set merging technique using inclusion-based fuzzy clustering

This paper proposes a new method of merging parameterized fuzzy sets based on clustering in the parameters space, taking into account the degree of inclusion of each fuzzy set in the cluster prototypes. The merger method is applied to fuzzy rule base simplification by automatically replacing the fuzzy sets corresponding to a given cluster with that pertaining to cluster prototype. The feasibility and the performance of the proposed method are studied using an application in mobile robot navigation. The results indicate that the proposed merging and rule base simplification approach leads to good navigation performance in the application considered and to fuzzy models that are interpretable by experts. In this paper, we concentrate mainly on fuzzy systems with Gaussian membership functions, but the general approach can also be applied to other parameterized fuzzy sets

An analytic framework to assess organizational resilience

Background: Resilience Engineering is a paradigm for safety management that focuses on coping with complexity to achieve success, even considering several conflicting goals. Modern socio-technical systems have to be resilient to comply with the variability of everyday activities, the tight-coupled and underspecified nature of work and the nonlinear interactions among agents. At organizational level, resilience can be described as a combination of four cornerstones: monitoring, responding, learning and anticipating. Methods: Starting from these four categories, this paper aims at defining a semi-quantitative analytic framework to measure organizational resilience in complex socio-technical systems, combining the Resilience Analysis Grid (RAG) and the Analytic Hierarchy Process (AHP). Results: This paper presents an approach for defining resilience abilities of an organization, creating a structured domain-dependent framework to define a resilience profile at different levels of abstraction, to identify weaknesses and strengths of the system and thus potential actions to increase system’s adaptive capacity. An illustrative example in an anaesthesia department clarifies the outcomes of the approach. Conclusions: The outcome of the RAG, i.e. a weighted set of probing questions, can be used in different domains, as a support tool in a wider Safety-II oriented managerial action to bring safety management into the core business of the organization

Multicriteria Fuzzy Analysis for a GIS-Based Management of Earthquake Scenarios

Objective of this article is the formulation andthe implementation of a decision-making model for theoptimal management of emergencies. It is based on theaccurate definition of possible scenarios resulting fromprediction and prevention strategies and explicitly takesinto account the subjectivity of the judgments of prefer-ence. To this end, a multicriteria decision model, basedon fuzzy logic, has been implemented in a user-friendlygeographical information system (GIS) platform so asto allow for the automation of choice processes betweenseveral alternatives for the spatial location of the investi-gated scenarios. In particular, we have analyzed the po-tentialities of the proposed approach in terms of seismicrisk reduction, simplifying the decision process leadingto the actions to be taken from directors and managers ofcoordination services. Due to the large number of vari-ables involved in the decision process, it has been pro-posed a particularly flexible and streamlined method inwhich the damage scenarios, based on the vulnerabilityof the territory, have represented the input data to de-rive a vector of weights to be assigned to different de-cision alternatives. As an application of the proposedapproach, the seismic damage scenario of a region of400 km2, hit by the 2009 earthquake in L’Aquila (Italy),has been analyzed

Landslide susceptibility mapping using multi-criteria evaluation techniques in Chittagong Metropolitan Area, Bangladesh

Landslides are a common hazard in the highly urbanized hilly areas in Chittagong Metropolitan Area (CMA), Bangladesh. The main cause of the landslides is torrential rain in short period of time. This area experiences several landslides each year, resulting in casualties, property damage, and economic loss. Therefore, the primary objective of this research is to produce the Landslide Susceptibility Maps for CMA so that appropriate landslide disaster risk reduction strategies can be developed. In this research, three different Geographic Information System-based Multi-Criteria Decision Analysis methods—the Artificial Hierarchy Process (AHP), Weighted Linear Combination (WLC), and Ordered Weighted Average (OWA)—were applied to scientifically assess the landslide susceptible areas in CMA. Nine different thematic layers or landslide causative factors were considered. Then, seven different landslide susceptible scenarios were generated based on the three weighted overlay techniques. Later, the performances of the methods were validated using the area under the relative operating characteristic curves. The accuracies of the landslide susceptibility maps produced by the AHP, WLC_1, WLC_2, WLC_3, OWA_1, OWA_2, and OWA_3 methods were found as 89.80, 83.90, 91.10, 88.50, 90.40, 95.10, and 87.10 %, respectively. The verification results showed satisfactory agreement between the susceptibility maps produced and the existing data on the 20 historical landslide locations

Geo-spatial Technology for Landslide Hazard Zonation and Prediction

Similar to other geo hazards, landslides cannot be avoided in mountainous terrain. It is the most common natural hazard in the mountain regions and can result in enormous damage to both property and life every year. Better understanding of the hazard will help people to live in harmony with the pristine nature. Since India has 15% of its land area prone to landslides, preparation of landslide susceptibility zonation (LSZ) maps for these areas is of utmost importance. These susceptibility zonation maps will give the areas that are prone to landslides and the safe areas, which in-turn help the administrators for safer planning and future development activities. There are various methods for the preparation of LSZ maps such as based on Fuzzy logic, Artificial Neural Network, Discriminant Analysis, Direct Mapping, Regression Analysis, Neuro-Fuzzy approach and other techniques. These different approaches apply different rating system and the weights, which are area and factors dependent. Therefore, these weights and ratings play a vital role in the preparation of susceptibility maps using any of the approach. However, one technique that gives very high accuracy in certain might not be applicable to other parts of the world due to change in various factors, weights and ratings. Hence, only one method cannot be suggested to be applied in any other terrain. Therefore, an understanding of these approaches, factors and weights needs to be enhanced so that their execution in Geographic Information System (GIS) environment could give better results and yield actual ground like scenarios for landslide susceptibility mapping. Hence, the available and applicable approaches are discussed in this chapter along with detailed account of the literature survey in the areas of LSZ mapping. Also a case study of Garhwal area where Support Vector Machine (SVM) technique is used for preparing LSZ is also given. These LSZ maps will also be an important input for preparing the risk assessment of LSZ