Geospatial databases generally consist of measurements related to points (or pixels in the case of raster data), lines, and polygons. In recent years, the size and complexity of these databases have increased signific...
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ISBN:
(纸本)0780379187
Geospatial databases generally consist of measurements related to points (or pixels in the case of raster data), lines, and polygons. In recent years, the size and complexity of these databases have increased significantly and they often contain duplicate records, i.e., two or more close records representing the same measurement result. In this paper we use fuzzy measures to address the problem of detecting duplicates in a database consisting of point measurements. As a test case, we use a database of measurements of anomalies in the Earth's gravity field that we have compiled. We show that a natural duplicate deletion algorithm requires (in the worst case) quadratic time, and we propose a new asymptotically optimal O(***(n)) algorithm. These algorithms have been successfully applied to gravity databases. We believe that they will prove to be useful when dealing with many other types of point data.
Fuzzy logic controllers have been proven to be an effective means of solving real world control issues. One of the difficulties in the construction of fuzzy controllers is the design of the rule base under which they ...
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Fuzzy logic controllers have been proven to be an effective means of solving real world control issues. One of the difficulties in the construction of fuzzy controllers is the design of the rule base under which they operate. This paper investigates the application of evolutionary programming as an iterative learning process for the fuzzy rule base. This approach is applied to the problem of an elevator control system. The system is optimized for efficiency and smoothness by encouraging higher velocities with minimal changes in acceleration, and by discouraging violations of the design parameters for the system. The performance of the evolved system compares favorably to that of fuzzy controllers designed using traditional methods.
Implementation of a fuzzy logic controller on an FPGA using VHDL is presented in this paper. The basic components of the fuzzy logic controller are designed using VHDL and a Xilinx virtex FPGA is used for implementati...
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Implementation of a fuzzy logic controller on an FPGA using VHDL is presented in this paper. The basic components of the fuzzy logic controller are designed using VHDL and a Xilinx virtex FPGA is used for implementation. The fuzzy logic controller with an 8-bit input, 8-bit output is tested by controlling single disk of an ECP torsional plant.
This paper presents an application of the fuzzy logic theory for the prediction of the soil strength depth variation due to aging effects. The results of experimental tests with reconstituted clayey soils of the Bay o...
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This paper presents an application of the fuzzy logic theory for the prediction of the soil strength depth variation due to aging effects. The results of experimental tests with reconstituted clayey soils of the Bay of Campeche in Mexico were used for the fuzzy rule-based system training. The Evolutionary Strategy (ES) was employed as an optimization method for the learning of the Mamdani-type fuzzy rule base. Fuzzy logic provides an easy and transparent method for incorporating common-sense type reasoning. The fuzzy logic model is based on a decision (inference) process that can be better described on a linguistic level using rules with soft facts. In this manner the clay soil strength through the time could be fuzzily predicted as a function of the mean effective normal stress, the time of consolidation and the water content. Illustrative examples showed that the result of prediction seems to be acceptable in engineering practice.
This paper addresses the problem of determining optimal overbooking policies on a single flight leg with multiple daily flights. In particular, it solves for the optimal booking level to accept on each of n daily flig...
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ISBN:
(纸本)0889863393
This paper addresses the problem of determining optimal overbooking policies on a single flight leg with multiple daily flights. In particular, it solves for the optimal booking level to accept on each of n daily flights from an origin to a destination point that minimizes the total cost of denied boarding and revenue losses. The problem is modeled and solved as a stochastic dynamic program where optimal overbooking policies for a single origin-destination flight leg are derived for up to 3 daily flights. An example illustrating the computation of optimal booking levels using the policies derived from the proposed model is shown for the case of Middle East Airlines daily flights on the Paris-Beirut leg.
A recent trend has seen the extension of object-oriented middleware to component-oriented middleware. A major advantage components offer over objects is that only the business logic of an application needs to be addre...
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A simple intrusion detection system (IDS) with respect to perception of human experts is proposed. Its computational framework is designed based on concepts of computational theory of perceptions (CTP) and mass assign...
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A simple intrusion detection system (IDS) with respect to perception of human experts is proposed. Its computational framework is designed based on concepts of computational theory of perceptions (CTP) and mass assignment theory (MAT). CTP provides a computational framework of representing and handling perception using linguistic terms and corresponding fuzzy sets. MAT provides that of representing and handling a bias consisting in between perception and observed intrusions through the consistency management between fuzzy sets and probability distributions. For the knowledge construction of this IDS, only linguistic descriptions extracted from organization policies and perception of human experts is expected. For the inference and refinement of knowledge, support logic, a truth functional logic for manipulating probability intervals, is used.
In this paper, the designed schemes for a two Mamdani fuzzy controllers, employing the scaling factor tuning are proposed. The first fuzzy logic controller, is a normalized controller used to control the system, the t...
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ISBN:
(纸本)0889863393
In this paper, the designed schemes for a two Mamdani fuzzy controllers, employing the scaling factor tuning are proposed. The first fuzzy logic controller, is a normalized controller used to control the system, the tuning for its input and output-scaling factors is done through the second fuzzy controller (the supervisory controller) used to appropriately determine the control signal of the fuzzy controllers. The supervisory fuzzy controller tunes the normalized fuzzy controller based on the model reference adaptive control technique. The great advantage of the proposed method is that, a supervisor as a fuzzy controller to tune the scaling factor of a normalized fuzzy controller can be used to supervise any standard controller (with fixed parameters). This may be applied to control any process in the distributed control systems (DCS). The normalized fuzzy controller and the supervisory fuzzy controller are organized with specific experience information about the controlled systems. Finally, the proposed fuzzy controllers are applied practically to control a nonlinear thermal process;a comparison with scaling factor manual tuning, supervisor with step reference input and supervisor with desired model reference input is done to verify the effectiveness of the proposed design. The results shows that the last case the system is forced to follow the desired response.
The proceedings contain 96 papers. The topics discussed include: hierarchical intelligent control of modular manipulators part a: neurofuzzy control design;fuzzy-neuro system for bridge health monitoring;deducing fuzz...
ISBN:
(纸本)0780379187
The proceedings contain 96 papers. The topics discussed include: hierarchical intelligent control of modular manipulators part a: neurofuzzy control design;fuzzy-neuro system for bridge health monitoring;deducing fuzzy inference systems with different numbers of membership functions from a neuro-fuzzy;a new method for fuzzy inference in intuitionistic fuzzy systems;looking for fuzziness in natural language;an information theoretic approach to generating membership functions from real data;evolving fuzzy controllers through evolutionary programming;additivity, noninteraction and semirings;fuzzy symmetric group categories in system sciences;and mathematical analysis of similarity index and connectivity index in fuzzy graph.
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