Showing 1–12 of 158 results
A Bluetooth Routing Protocol Using Evolving Fuzzy Neural Networks
In this paper, a rouادامه/دانلودرایگان!
In this paper, a routing protocol which utilizes the characteristics of Bluetooth technology is proposed for Bluetooth-based mobile ad hoc networks. The routing tables are maintained in the master devices and the routing zone radius for each table is adjusted dynamically by using evolving fuzzy neural networks. Observing there exists some useless routing packets which are helpless to build the routing path and increase the network loads in the existing ad hoc routing protocols, we selectively use multiple unicasts or one broadcast when the destination device is out of the routing zone radius coverage of the routing table. The simulation results show that the dynamic adjustment of the routing table size in each master device results in much less reply time of routing request, fewer request packets and useless packets compared with two representative protocols, Zone Routing Protocol and Dynamic Source Routing
A comparison of neural network models, fuzzy logic, and multiple linear regression for prediction of hatchability
Application of approادامه/دانلودرایگان!
Application of appropriate models to approximate the performance function warrants more precise prediction and helps to make the best decisions in the poultry industry. This study reevaluated the factors affecting hatchability in laying hens from 29 to 56 wk of age. Twenty-eight data lines representing 4 inputs consisting of egg weight, eggshell thickness, egg sphericity, and yolk/albumin ratio and 1 output, hatchability, were obtained from the literature and used to train an artificial neural network (ANN). The prediction ability of ANN was compared with that of fuzzy logic to evaluate the fitness of these 2 methods. The models were compared using R2, mean absolute deviation (MAD), mean squared error (MSE), mean absolute percentage error (MAPE), and bias. The developed model was used to assess the relative importance of each variable on the hatchability by calculating the variable sensitivity ratio. The statistical evaluations showed that the ANN-based model predicted hatchability more accurately than fuzzy logic. The ANNbased model had a higher determination of coefficient (R2 = 0.99) and lower residual distribution (MAD = 0.005; MSE = 0.00004; MAPE = 0.732; bias = 0.0012) than fuzzy logic (R2 = 0.87; MAD = 0.014; MSE = 0.0004; MAPE = 2.095; bias = 0.0046). The sensitivity analysis revealed that the most important variable in the ANN-based model of hatchability was egg weight (variable sensitivity ratio, VSR = 283.11), followed by yolk/albumin ratio (VSR = 113.16), eggshell thickness (VSR = 16.23), and egg sphericity (VSR = 3.63). The results of this research showed that the universal approximation capability of ANN made it a powerful tool to approximate complex functions such as hatchability in the incubation process
A Configurational Comparative Method to Identify Multiple Pathways to Improve Patient-Centered Medical Home Models
This brief focuses oادامه/دانلودرایگان!
This brief focuses on using fuzzy set Qualitative Comparative Analysis (fsQCA) to evaluate patientcentered medical home (PCMH) models. It is part of a series commissioned by the Agency for Healthcare Research and Quality (AHRQ) and developed by Mathematica Policy Research under contract, with input from other nationally recognized thought leaders in research methods and PCMH models. The series is designed to expand the toolbox of methods used to evaluate and refine PCMH models. The PCMH is a primary care approach that aims to improve quality, cost, and patient and provider experience. PCMH models emphasize patient-centered, comprehensive, coordinated, accessible care, and a systematic focus on quality and safety
A data mining approach for grouping and analyzing trajectories of care using claim data
Background: With th...ادامه/دانلودرایگان!
Background: With the increasing burden of chronic diseases, analyzing and understanding trajectories of care is essential for efficient planning and fair allocation of resources. We propose an approach based on mining claim data.to support the exploration of trajectories of car
Methods: A clustering of trajectories of care for breast cancer was performed with Formal Concept Analysis. We exported Data from the French national casemix system, covering all inpatient admissions in the country. Patients admitted for breast cancer surgery in 2009 were selected and their trajectory of care was recomposed with all hospitalizations occuring within one year after surgery. The main diagnoses of hospitalizations were used to produce morbidity profiles. Cumulative hospital costs were computed for each profile
A Framework for Reasoning with Expressive Continuous Fuzzy Description Logics
In the current paperادامه/دانلودرایگان!
In the current paper we study the reasoning problem for fuzzy SI (f-SI) under arbitrary continuous fuzzy operators. Our work can be seen as an extension of previous works that studied reasoning algorithms for f-SI, but focused on specific fuzzy operators, e.g. fKD–SI and of reasoning algorithms for less expressive fuzzy DLs, like fL–ALC and fP –ALC (fuzzy ALC under the Lukasiewicz and product fuzzy operators, respectively). We show how transitivity can be handled for all the range of continuous fuzzy DLs and discuss about blocking and correctness in this setting. Based on these analysis, we present a unifying framework for reasoning over the class of continuous fuzzy DLs. Finally use the results to prove decidability of several fuzzy SI DLs
A FUZZY AHP APPROACH FOR SUPPLIER SELECTION PROBLEM: A CASE STUDY IN A GEARMOTOR COMPANY
Supplier selection iادامه/دانلودرایگان!
Supplier selection is one of the most important functions of a purchasing department. Since by deciding the best supplier, companies can save material costs and increase competitive advantage. However this decision becomes complicated in case of multiple suppliers, multiple conflicting criteria, and imprecise parameters. In addition the uncertainty and vagueness of the experts’ opinion is the prominent characteristic of the problem. Therefore an extensively used multi criteria decision making tool Fuzzy AHP can be utilized as an approach for supplier selection problem. This paper reveals the application of Fuzzy AHP in a gear motor company determining the best supplier with respect to selected criteria. The contribution of this study is not only the application of the Fuzzy AHP methodology for supplier selection problem, but also releasing a comprehensive literature review of multi criteria decision making problems. In addition by stating the steps of Fuzzy AHP clearly and numerically, this study can be a guide of the methodology to be implemented to other multiple criteria decision making problems
A fuzzy logic expert system to estimate intrinsic extinction vulnerabilities of marine fishes to fishing
Fishing has become aادامه/دانلودرایگان!
Fishing has become a major conservation threat to marine fishes. Effective conservation of threatened species requires timely identification of vulnerable species. However, evaluation of extinction risk using conventional methods is difficult for the majority of fish species because the population data normally required by such methods are unavailable. This paper presents a fuzzy expert system that integrates life history and ecological characteristics of marine fishes to estimate their intrinsic vulnerability to fishing. We extract heuristic rules (expressed in IF–THEN clauses) from published literature describing known relationships between biological characteristics and vulnerability. Input and output variables are defined by fuzzy sets which deal explicitly with the uncertainty associated with qualitative knowledge. Conclusions from different lines of evidence are combined through fuzzy inference and defuzzification processes. Our fuzzy system provides vulnerability estimates that correlate with observed declines more closely than previous methods, and has advantages in flexibility of input data requirements, in the explicit representation of uncertainty, and in the ease of incorporating new knowledge. This fuzzy expert system can be used as a decision support tool in fishery management and marine conservation planning
A Fuzzy Logic-based Personalized Learning System for Supporting Adaptive English Learning
As a nearly global lادامه/دانلودرایگان!
As a nearly global language, English as a Foreign Language (EFL) programs are essential for people wishing to learn English. Researchers have noted that extensive reading is an effective way to improve a person’s command of English. Choosing suitable articles in accordance with a learner’s needs, interests and ability using an elearning system requires precise learner profiles. This paper proposes a personalized English article recommending system, which uses accumulated learner profiles to choose appropriate English articles for a learner. It employs fuzzy inference mechanisms, memory cycle updates, learner preferences and analytic hierarchy process (AHP) to help learners improve their English ability in an extensive reading environment. By using fuzzy inferences and personal memory cycle updates, it is possible to find an article best suited for both a learner’s ability and her/his need to review vocabulary. After reading an article, a test is immediately provided to enhance a learner’s memory for the words newly learned in the article. The responses of tests can be used to explicitly update memory cycles of the newly-learned vocabulary. In addition, this paper proposes a methodology that also implicitly modifies memory cycles of words that were learned before. By intensively reading articles recommended through the proposed approach, learners comprehend new words quickly and review words that they knew implicitly as well, thereby efficiently improving their vocabulary volume. Analyses of learner achievements and questionnaires have confirmed that the adaptive learning method presented in this study not only enhances the English ability of learners but also helps maintaining their learning interest
A fuzzy pert approach to evaluate plant construction project scheduling risk under uncertain resources capacity
A plant constructionادامه/دانلودرایگان!
A plant construction project always involves lots of activities. Precise information about the activities duration is unfortunately unavailable due to the uncertain resources capacity. The fuzzy program evaluation and review technique (PERT) has been widely applied to solve the fuzzy project scheduling problem. This paper presents an extended fuzzy PERT approach with four major improvement aspects to support the construction project scheduling management: 1) Evaluate operation fuzzy times based on available working volumes, resources quantity and fuzzy capacity of resources, 2) Adopting a maximal i levelcut method to compare the fuzzy precedent activities times to determine the reasonable earliest starting times of each activity, 3) Using fuzzy algebra method instead of fuzzy subtraction method to compute the fuzzy latest starting times and 4) Developing a project scheduling risk index (PSRI) to assist the decision maker to evaluate the project scheduling risk. Simulations experiments are conducted and demonstrated satisfactory results
A fuzzy set-based accuracy assessment of soft classi®cation
Despite the sizableادامه/دانلودرایگان!
Despite the sizable achievements obtained, the use of soft classi®ers is still limited by the lack of well-assessed and adequate methods for evaluating the accuracy of their outputs. This paper proposes a new method that uses the fuzzy set theory to extend the applicability of the traditional error matrix method to the evaluation of soft classi®ers. It is designed to cope with those situations in which classi®cation and/or reference data are expressed in multimembership form and the grades of membership represent dierent levels of approximation to intrinsically vague classes. Ó 1999 Elsevier Science B.V. All rights reserved
A Fuzzy Vault Scheme
We describe a simpleادامه/دانلودرایگان!
We describe a simple and novel cryptographic construction that we refer to as a fuzzy vault. A player Alice may place a secret value κ in a fuzzy vault and “lock” it using a set A of elements from some public universe U. If Bob tries to “unlock” the vault using a set B of similar length, he obtains κ only if B is close to A, i.e., only if A and B overlap substantially. In constrast to previous constructions of this flavor, ours possesses the useful feature of order invariance, meaning that the ordering of A and B is immaterial to the functioning of the vault. As we show, our scheme enjoys provable security against a computationally unbounded attacker
A Hierarchical Fuzzy Classification of Online Customers
A key challenge forادامه/دانلودرایگان!
A key challenge for companies in the e-business era is to manage customer relationships as an asset. In today’s global economy this task is getting, at the same time, more difficult and more important. In order to retain the potentially good customers and to improve their buying attitude this paper proposes a hierarchical fuzzy classification of online customers. A fuzzy classification, which is a combination of relational databases and fuzzy logic, allows customers to be classified in several classes at the same time and can therefore precisely determine the customers’ value for an enterprise. This approach allows companies to improve the customer equity, to launch loyalty programs, to automate mass customization and to refine marketing campaigns in order to maximize the customers’ value and, this way, the companies’ profit