Recently, data management and processing for wireless sensor networks (WSNs) has become a topic of active research in several fields of computer science, such as the distributed systems, the database systems, and the ...
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Recently, data management and processing for wireless sensor networks (WSNs) has become a topic of active research in several fields of computer science, such as the distributed systems, the database systems, and the data mining. The main aim of deploying the WSNs-based applications is to make the real-time decision which has been proved to be very challenging due to the highly resource-constrained computing, communicating capacities, and huge volume of fast-changed data generated by WSNs. This challenge motivates the research community to explore novel data mining techniques dealing with extracting knowledge from large continuous arriving data from WSNs. Traditional data mining techniques are not directly applicable to WSNs due to the nature of sensor data, their special characteristics, and limitations of the WSNs. This work provides an overview of how traditional data mining algorithms are revised and improved to achieve good performance in a wireless sensor network environment. A comprehensive survey of existing data mining techniques and their multilevel classification scheme is presented. The taxonomy together with the comparative tables can be used as a guideline to select a technique suitable for the application at hand. Based on the limitations of the existing technique, an adaptive data mining framework of WSNs for future research is proposed.
This paper deals with global optimization. There are many algorithms for global optimization in the literature. In this text, we focus on two effective optimizers. The first one is an adaptive version of Differential ...
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The main objective of this paper is to provide a state-of-the-art survey of advanced optimization methods used in machine learning. It starts with a short introduction to machine learning followed by the formulation o...
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This book constitutes the refereed proceedings of the internationalworkshop on Approximation algorithms for Combinatorical optimization, APPROX'98, held in conjunction with ICALP'98 in Aalborg, Denmark, in Ju...
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ISBN:
(数字)9783540690672
ISBN:
(纸本)9783540647362
This book constitutes the refereed proceedings of the internationalworkshop on Approximation algorithms for Combinatorical optimization, APPROX'98, held in conjunction with ICALP'98 in Aalborg, Denmark, in July 1998.;The volume presents 14 revised full papers together with three invited papers selected from 37 submissions. The papers address the design and analysis of approximation algorithms, inapproximability results, on-line problems, randomization techniques, average-case analysis, approximation classes, scheduling problems, routing and flow problems, coloring and partitioning, cuts and connectivity, packing and covering, geometric problems, network design, and various applications.
The proceedings contain 34 papers. The topics discussed include: harmonic filters planning of system for specially connected transformers using PSO-NTVE method;emotion orientated recommendation system for Hiroshima to...
ISBN:
(纸本)9781467357265
The proceedings contain 34 papers. The topics discussed include: harmonic filters planning of system for specially connected transformers using PSO-NTVE method;emotion orientated recommendation system for Hiroshima tourist by fuzzy Petri net;an estimation of favorite value in emotion generating calculation by fuzzy Petri net;development of automatic positioning system for bicycle saddle based on lower limb's EMG signals during pedaling motion;dependent input neuron selection in contradiction resolution;location-based burst detection algorithm for geo-referenced document streams based on user's moving direction;meta-heuristic algorithms applied to the optimization of type-1 and type 2 TSK fuzzy logic systems for sea water level prediction;interval-valued differential evolution for evolving neural networks with interval weights and biases;and structural optimization of neural network for data prediction using dimensional compression and tabu search.
The planning of an optimal design of routes is a complex problem of optimization and belongs to the type of NP-Hard problems. In this case, to find an exact solution is nonviable, and, therefore, it needs methods that...
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ISBN:
(纸本)9783540876557
The planning of an optimal design of routes is a complex problem of optimization and belongs to the type of NP-Hard problems. In this case, to find an exact solution is nonviable, and, therefore, it needs methods that assure the optimal management of the real resources to the design of the new routes under the best criteria about times and costs. This paper proposes the use of heuristic algorithms bio-inspired for the optimization in the design of the routes under diverse restrictions in the collective urban public transport in a town. This is because there are many applications in the transport field where this type of heuristic have proved to be very efficient. Moreover, among the variables that have greatest impact in developing this work, is the passenger demand, seen as uncertain data. For his treatment, it is suggested the use of the Fuzzy Sets Theory. Therefore, the purpose of this study is to establish a model for solving a complex and uncertain problem.
The program of optimal quantization of a continuous distribution suggested by Heitsch H. and W. Romisch in 2003 is generalized for arbitrage exclusion in financial models. It is a non-convex problem, which belongs to ...
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Power consumption and portability issues are increasingly significant in system-on-a-chip applications. As a result, it is important that power and performance tradeoffs are made more visible to chip architects and ci...
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ISBN:
(纸本)076951944X
Power consumption and portability issues are increasingly significant in system-on-a-chip applications. As a result, it is important that power and performance tradeoffs are made more visible to chip architects and circuit designers. Next generation tools are being developed to achieve high accuracy by estimating power consumption earlier in the design process. These tools also allow the designer to explore different configurations in a given design space. As the design space continues to expand. more efficient search methods are needed This paper presents a framework for an evolutionary approach to configuring an ideal embedded processor based on power consumption.
Motivated by questions in property testing, we search for linear error-correcting codes that have the "single local orbit" property: they are specified by a single local constraint and its translations under...
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ISBN:
(纸本)9783642036842
Motivated by questions in property testing, we search for linear error-correcting codes that have the "single local orbit" property: they are specified by a single local constraint and its translations under the symmetry group of the code. We show that the dual of every "sparse" binary code whose coordinates are indexed by elements of F-2n for prime n, and whose symmetry group includes the group of non-singular affine transformations of F-2n, has the single local orbit property. (A code is sparse if it contains polynomially many codewords in its block length.) In particular this class includes the dual-BCH codes for whose duals (BCH codes) simple bases were not known. Our result gives the first short (O(n)-bit, as opposed to exp(n)-bit) description of a low-weight basis for BCH codes. If 2(n) - 1 is a Mersenne prime, then we get that every sparse cyclic code also has the single local orbit.
Hysteresis cellular neural networks are one of artificial neural networks which work effectively against large scale problems. In the previous work, remarkable methods have never been developed to overcome the defects...
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ISBN:
(纸本)981238121X
Hysteresis cellular neural networks are one of artificial neural networks which work effectively against large scale problems. In the previous work, remarkable methods have never been developed to overcome the defects of hysteresis cellular neural networks. We then propose a novel architecture for combinatorial optimization problems to overcome them. Experimental results indicate the efficiency of the architecture.
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