Current Issue : July - September Volume : 2015 Issue Number : 3 Articles : 7 Articles
In many real world data analysis tasks, it is expected that we can get much more useful knowledge by utilizing multiple\ndatabases stored in different organizations, such as cooperation groups, state organs, and allied countries. However, in many\nsuch organizations, they often hesitate to publish their databases because of privacy and security issues although they believe\nthe advantages of collaborative analysis. This paper proposes a novel collaborative framework for utilizing vertically partitioned\ncooccurrence matrices in fuzzy co-cluster structure estimation, in which cooccurrence information among objects and items is\nseparately stored in several sites. In order to utilize such distributed data sets without fear of information leaks, a privacy preserving\nprocedure is introduced to fuzzy clustering for categorical multivariate data (FCCM).Withholding each element of cooccurrence\nmatrices, only object memberships are shared by multiple sites and their (implicit) joint co-cluster structures are revealed through\nan iterative clustering process. Several experimental results demonstrate that collaborative analysis can contribute to revealing\nglobal intrinsic co-cluster structures of separate matrices rather than individual site-wise analysis. The novel framework makes it\npossible for many private and public organizations to share common data structural knowledge without fear of information leaks....
A model is developed using fuzzy probability to screen survey data across relevant criteria for selecting suppliers based on fuzzy\nexpected values. The values are derived from qualitative variables and expert opinion of membership in these variables found in\nindustry survey data. The application is made to a supply chain management decision of supplier selection based upon delivery\nperformance which is further divided into attributes that comprise this criterion. The algorithm allows multiple criteria to be\nconsidered for each decision parameter. Large sets of survey data regarding six suppliers in the electronic parts industry are gathered\nfrom over 150 purchasers and are analyzed through spreadsheet modeling of the fuzzy algorithm. The resulting decision support\nsystem allows supply chain managers to improve supplier selection decisions by applying fuzzy measures of criteria and associated\nbeliefs across the dataset. The proposed model and method are highly adaptable to existing survey datasets, including datasets that\nhave incomplete data, and can be implemented in organizations with low decision support resources, such as small and medium\nsized organizations....
This paper presents a novel analytical approach to evaluating continuous, nonmonotonic functions of independent fuzzy numbers.\nThe approach is based on a parametric ????-cut representation of fuzzy numbers and allows for the inclusion of parameter uncertainties\ninto mathematical models....
The exponentially stabilizing state feedback control algorithm is developed by Lyapunov�s second method leading to the variable\nstructure system with chattering free sliding modes. Linear time-invariant discrete-time second order plant is considered and the\ncontrol law is obtained by using a simple fuzzy controller.The analytical structure of the proposed controller is derived and used\nto prove exponential stability of sliding subspace. Essentially, the control algorithm drives the system from an arbitrary initial state\nto a prescribed so-called sliding subspace S, in finite time and with prescribed velocity estimate. Inside the sliding subspace S, the\nsystem is switched to the sliding mode regime and stays in it forever.The proposed algorithm is tested on the real system in practice,\nDC servo motor, and simulation and experimental results are given....
Mobile ad-hoc network is a network without communications where every node has its own protocols and services for powerful collaboration in the network. The wireless links in MANET are highly error prone and can go down frequently due to mobility of nodes, interference and less infrastructure. Routing in MANET is a critical task due to highly lively environment. Hence, fuzzy logic is applied to supervise routing policies and to enhance routing performance dynamically. The parameters (energy, bandwidth, mobility and packet forwarding ratio) in MANET were classified with fuzzy degree of association. The algorithm was developed and simulated using NS2. The results of the simulation showed that the performance of the FMRC algorithm was noticeably improved compared with FBR. Hence, it is feasible that the fuzzy logic multipath congestion control algorithm is applied to optimize routing performance of MANET....
20 samples and 44 samples of terracotta warriors and horses from the 1st and 3rd pits of Qin Shihuang�s Mausoleum, 20 samples\nof clay near Qin�s Mausoleum, and 2 samples of Yaozhou porcelain bodies are obtained to determine the contents of 32 elements\nin each of them by neutron activation analysis (NAA). The NAA data are further analyzed using fuzzy cluster analysis to obtain\nthe fuzzy cluster trend diagram. The analysis shows that the origins of the raw material of the terracotta warriors and horses from\n1st and 3rd pits are not exactly the same but are closely related to the loam soil layer near Qin�s Mausoleum while distant from the\nloess layers in the same area and remotely related to the Yaozhou porcelain bodies. It can be concluded that the raw material of the\nterracotta warriors and horses was taken from certain loam layer near Qin�sMausoleum and the kiln sites might be located nearby....
Comprehensive and predictive modeling of submicron devices using the traditional TCAD EDA tools of device simulation has\nbecome increasingly perplexing due to a lack of reliable models and difficulties in calibrating available device models. This paper\nproposes a new technique to model BCD submicron pMOSFET devices and to predict device behaviors under different bias\nconditions and different geometry dimensions by using the adaptive neurofuzzy inference system (ANFIS), which combines fuzzy\ntheory and adaptive neuronet working. Here, the power of using ANFIS to realize the I-V behaviors is demonstrated in these p channel\nMOS transistors. After a systematic evaluation, it can be found that the predicting results of I-V behaviors of complicated\nsub micron pMOSFETs by ANFIS are compared with the actual diagnostic experiment data, and a good agreement has been\nobtained. Furthermore, the error percentage was no greater than 2.5%. As such, the demonstrated benefits of this new proposed\ntechnique include precise prediction and easier implementation....
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