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Application of Fuzzy Cognitive Maps to water demand prediction

Application of Fuzzy Cognitive Maps to water demand predicti...

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IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： Papageorgiou, Elpiniki I. Poczeta, Katarzyna Laspidou, Chrysi CERTH Ctr Res & Technol Hellas Inst Informat Technol 6th Km Charilaou Thermi Rd Thermi 57001 Greece Technol Educ Inst TEI Cent Greece Dept Comp Engn Lamia 35100 Greece Kielce Univ Technol Dept Comp Sci Applicat Kielce Poland Univ Thessaly Dept Civil Engn Volos 38334 Volos Greece

ISBN: (纸本)9781467374286

this article is focused on the issue of learning of Fuzzy Cognitive Maps designed to model and predict time series. the multi-step supervised-learning based-on-gradient methods as well as population-based learning, with the use of real coded genetic algorithms, are described. In this study, a new structure optimization genetic algorithm for fuzzy cognitive maps learning is proposed for automatic construction of FCM applied to time series prediction. the proposed learning methodologies are based on an FCM reconstruction procedure using historical time series. the main contribution of this study is the analysis of the use of FCMs with their learning algorithms based on the multi-step gradient method (MGM) and other population-based methods to predict water demand. the performance of learning algorithms is presented through the analysis of real data of daily water demand and the corresponding prediction. the multivariate analysis of historical water demand data is held for five variables, mean and high temperature, precipitation, wind speed and touristic activity. Simulation results were obtained with the ISEMK (Intelligent Expert System based on Cognitive Maps) software tool. through the experimental analysis, we demonstrate the usefulness of the new proposed FCM learning algorithm in water demand prediction, by calculating the known prediction errors. the advantage of the optimization genetic algorithm structure is its ability to select the most significant relations between concepts for prediction.

关键词： Fuzzy Cognitive Maps Multi-Step Learning algorithms Population-Based Learning algorithms Real Coded Genetic Algorithm Structure Optimization Genetic Algorithm Gradient Method

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Enhancing the performance of Biogeography-based optimization in discrete domain 6th

Enhancing the performance of Biogeography-based optimization...

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6th international conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015

作者： Xu, Qingzheng Wang, Na Zhang, Jianhang Gu, Xiang Xi’an Communications Institute Xi’an710106 China

ISBN: (纸本)9783319204659

Oppositional Biogeography-Based Optimization using the Current Optimum (COOBBO) has been recently developed to solve combinatorial problems and outperforms other heuristic algorithms. the objective of this paper is mainly to ascertain various modified methods which can significantly enhance the performance and efficiency of COOBBO algorithm. the improvement measures include crossover approach, local optimization approach and greedy approach. Experiment results illustrate that, the combination model of "inverover crossover + 2-opt local optimization + all greedy" may be the best choice of all when considering both the overall algorithm performance and computation overhead. © Springer international Publishing Switzerland 2015.

关键词： Traveling salesman problem

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discrete-ordinates quadratures based on linear and quadratic discontinuous finite elements over spherical quadrilaterals

Discrete-ordinates quadratures based on linear and quadratic...

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mathematics and Computations, Supercomputing in Nuclear Applications and Monte Carlo international conference, M and C+SNA+MC 2015

作者： Lau, Cheuk Y. Adams, Marvin L. Texas A and M University 3133 TAMU College StationTX77843-3133 United States

ISBN: (纸本)9781510808041

We present LDFE/QDFE-SQ discrete-ordinates quadratures based on linear and quadratic discontinuous finite elements (LDFEIQDFE) over spherical quadrilaterals (SQ) on the unit sphere. the LDFE-SQ quadratures are an extension of the Jarrell-Adams LDFE-ST quadratures which use spherical triangles (ST). the use of SQ instead of ST produces more uniform quadrature ordinate distributions reducing local integration variability. the QDFE-SQ quadratures demonstrate higher-order (i.e., quadratic) basis functions can be used within the discontinuous finite-element based quadrature methodology. the LDFE-SQ (resp. QDFE-SQ) quadratures place four (resp. nine) ordinates in each SQ. the weight of each ordinate is the integral of its basis function over the SQ surface. the LDFE/QDFE-SQ quadratures exactly integrate all 2nd-order spherical harmonics and higher orders tested (up to 6th-order) with 4th-order accuracy. the LDFE/QDFE-SQ quadratures also integrate the scalar flux for a simple one-cell problem with 4th-order accuracy - significantly better than Level Symmetric (1.5-order) and GaussChebyshev (2nd-order) quadratures and on-par with the Quadruple Range quadrature (4th-order). the LDFE/QDFE-SQ error convergence becomes more complicated for the Kobayashi benchmark showing between 2nd and 3rd-order accuracy at intermediate refinement and rapid convergence at high refinement. Locally-refined LDFE-SQ quadratures show much fewer ordinates are needed for error reduction when refinement is confined to the required cone of angle. the LDFE/QDFE-SQ quadratures are well-suited for use in adaptive discrete-ordinates since they are locally refinable, have strictly positive weights, and can be generated for large numbers of directions. © Copyright (2015) by the American Nuclear Society.

关键词： Functions

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Rectilinear Path Problems in Restricted Memory Setup 1

Rectilinear Path Problems in Restricted Memory Setup

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1st international conference on algorithms and discrete applied mathematics (CALDAM)

作者： Bhattacharya, Binay K. De, Minati Maheshwari, Anil Nandy, Subhas C. Roy, Sasanka Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada Technion Israel Inst Technol Haifa Israel Carleton Univ Sch Comp Sci Ottawa ON K1S 5B6 Canada Indian Stat Inst Kolkata India Chennai Math Inst Madras Tamil Nadu India

ISBN: (纸本)9783319149745;9783319149738

We study the rectilinear path problem in the presence of disjoint axis parallel rectangular obstacles in the in-place and read-only setup. the input to the problem is a set R of n axis-parallel rectangular obstacles in IR2. We need to preprocess the members in R such that the following query can be answered efficiently. Path-Query(p, q): Given a pair of points p and q, report an axis-parallel path from p to q avoiding the obstacles in R. In the read-only setup, we consider a restricted version of the Path-Query(p, q) problem, where the objective is to check the existence of an xy-monotone path between the given pair of points p and q avoiding the obstacles, and report it if such a path exists. Given O(s) extra space, the problem can be solved in O(n(2)/s + n log s + M-s log n) time, where Ms is the time complexity for computing the median of n elements in read-only setup using O(s) extra space. In the in-place setup, we preprocess the input rectangles in a data structure such that for any pair of query points p and q, the problem Path-Query(p, q) can be solved efficiently. the time complexities for the preprocessing and query are O(n log n) and O(n(3/4) + chi) respectively, where chi is the number of links (bends) in the path. the extra space requirement for both preprocessing and query answering are O(1). We also show that among a set of unit square obstacles, there always exists a path of O(log n) links between a pair of query points. Here, we use a different in-place data structure with same preprocessing time complexity to answer the query in O(log n) time.

关键词： Rectilinear path problem in-place and read-only model of computation constant work-space

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Numerical modeling of posteriori algorithms for the geophysical monitoring 1

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8th international conference on Mathematical Modeling of Technological Processes, CITech 2015

作者： Voskoboynikova, Gyulnara Khairetdinov, Marat Institute of Computational Mathematics and Mathematical Geophysics Siberian Branch of Russian Academy of Sciences Lavrentiev Ave 6 Novosibirsk630090 Russia

ISBN: (数字)9783319250588

ISBN: (纸本)9783319250571

In this paper, some problems of geophysical monitoring of the natural environment are considered. Many of them involve online detection of natural and technogenic events and the preceding geodynamic processes developing in the Earth. Such events include earthquakes, volcano eruptions, lunar and solar tides, landslides, falls of celestial bodies, quarry explosions causing technogenic earthquakes, etc. A new approach to solving the problem of active geophysical monitoring of the natural environment is proposed and investigated. It is based on the detection and separation of waveforms generated in the Earth and surface atmosphere by the above events. the solution is obtained by a unifying process of discrete optimization. the efficiency of this approach is illustrated by some numerical experiments. © Springer international Publishing Switzerland 2015.

关键词： Inverse problems

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An Improved discrete Firefly and t-Test based Algorithm for Blind Image Steganalysis

An Improved Discrete Firefly and t-Test based Algorithm for ...

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international conference on Intelligent Systems, Modelling and Simulation (ISMS)

作者： Rita Rana Chhikara Latika Singh Dept of CSE/IT ITM University Gurgaon Haryana

Feature Selection is a preprocessing technique with great significance in data mining applications that aims at reducing computational complexity and increase predictive capability of a learning system. this paper presents a new hybrid feature selection algorithm based on discrete Firefly optimization technique with dynamic alpha and gamma parameters and t-test filter technique to improve detectability of hidden message for Blind Image Steganalysis. the experiments are conducted on important dataset of feature vectors extracted from frequency domain, discrete Cosine Transformation and discrete Wavelet Transformation domain of cover and stego images. the results from popular JPEG steganography algorithms nsF5, Outguess, PQ and JP Hide and Seek show that proposed method is able to identify sensitive features and reduce the feature set by 67% in DCT domain and 37% in DWT domain. the experiment analysis shows that these algorithms are most sensitive to Markov features from DCT domain and variance statistical moment from DWT domain.

关键词： Feature extraction discrete cosine transforms Accuracy discrete wavelet transforms Classification algorithms Algorithm design and analysis Heuristic algorithms

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M-band Wavelet Based Pseudo Quantum Watermarking

M-band Wavelet Based Pseudo Quantum Watermarking

引用

international conference on applied, Numerical and Computational mathematics

作者： TONG LIU XUAN XU XIAODI WANG Department of Math Tsinghua University Department of Chemistry Hong Kong University of Science and Technology Department of Math Western Connecticut State University

ISBN: (纸本)9781618043283

Computational methods derived from digital signal processing are playing a significant role in the security and copyrights of audio, video, and visual arts. In light of the quantum computing, the corresponding algorithms are becoming a new research direction in today's high-technology world. the nature of quantum computer guarantees the security of quantum data, so a safe and effective quantum watermarking algorithm is in demand. Quantum watermarking is the technique that embeds the invisible quantum signal into quantum multimedia data for copyright protection. Different from most traditional algorithms, we propose new algorithms which apply a quantum or a pseudo quantum watermarking in M-band wavelet domain. Assured by the Heisenberg uncertainty principle and quantum no-cloning theorem, the security of quantum watermark can reach a very high-level standard. In other words, these watermarking algorithms can defeat nearly all attackers, no matter using classical computer or quantum computer.

关键词： discrete M-band wavelet transforms (DMWT) Quantum and pseudo watermarks Quantum computing Quantum and pseudo Images quantum computing quanta Watermarking Quantum computers M-line Visual arts copyrights audio video Uncertainty principle Security Digital signal processing computational methods algorithms Pseudo

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Fuzzy set interpretation of comparator networks 6th

Fuzzy set interpretation of comparator networks

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6th international conference on Pattern Recognition and Machine Intelligence, PReMI 2015

作者： Sosnowski, Lukasz Ślęzak, Dominik Systems Research Institute Polish Academy of Sciences Ul. Newelska 6 Warsaw01-447 Poland Dituel Sp. z o.o Ul. Ostrobramska 101 Lok. 206 Warsaw04-041 Poland Institute of Mathematics University of Warsaw Ul. Banacha 2 Warsaw02-097 Poland Infobright Inc Ul. Krzywickiego 34 Lok. 219 Warsaw02-078 Poland

We discuss how to model similarities between compound objects by utilizing networks of comparators. the framework is used to construct identification and classification systems. Comparing to our previous research, we pay a special attention to fuzzy-set-inspired foundations of how compound signals are processed through the network. We also reconsider some of already-known examples of applications of comparator networks, now using the proposed fuzzy-set-based terminology. © Springer international Publishing Switzerland 2015.

关键词： Comparators (optical)

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A discrete event simulation model of an emergency department network for earthquake conditions

A discrete event simulation model of an emergency department...

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international conference on Modeling, Simulation and applied Optimization (ICMSAO)

作者： Muhammet Gul Ali Fuat Guneri Department of Industrial Engineering Yildiz Technical University Istanbul Turkey

Emergency departments (EDs) are the first admission points of hospitals for patients (victims) during normal and disaster conditions. To meet the uncertain patient demand, make the first examination, discharge or admit into impatient units are included in responsibility of these departments. Resource design of emergency departments in order to struggle patient surge for earthquake disaster conditions affects ED performance measures such as patient length of stay (LOS), human and treatment area utilization and queue length. In this study, an ED network consisting of five public hospital emergency departments where located in the earthquake zone of Istanbul is modeled by discrete event simulation (DES). the aim of the study is to (1) model the ED network for normal conditions, (2) generate earthquake related scenarios, and (3) develop a health care decision and policy making tool for stakeholders.

关键词： Earthquakes Analytical models Computational modeling Data models Hospitals Surges

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Application of data mining in air traffic forecasting 15

Application of data mining in air traffic forecasting

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15th AIAA Aviation Technology, Integration, and Operations conference, 2015

作者： Busquets, Judit G. Alonso, Eduardo Evans, Antony D. City University London LondonEC1V 0HB United Kingdom University of California Santa Cruz Moffett FieldCA94035 United States Air Transport Engineering United Kingdom School of Mathematics Computer Science and Engineering United States University Affiliated Research Center MS210-6 United Kingdom

ISBN: (数字)9781624103698

ISBN: (纸本)9781624103698

the main goal of the study centers on developing a model for the purpose of air traffic forecasting by using off-the-shelf data mining and machine learning techniques. Although data driven modeling has been extensively applied in the aviation sector, little research has been done in the area of air traffic forecasting. this study is inspired by previous research focused on improving the Federal Aviation Administration (FAA) Terminal Area Forecasting (TAF) methodology, which historically assumed that the US air transportation system (ATS) network structure was static. Recent developments use data mining algorithms to predict the likelihood of previously un-connected airport-pairs being connected in the future, and the likelihood of connected airport-pairs becoming un-connected. Despite the innovation of this research, it does not focus on improving the FAA’s existing methodology for forecasting future air traffic levels on existing routes, which is based on relatively simple regression and growth models. We investigate different approaches for improving and developing new features within the existing data mining applications in air traffic forecasting. We focus particularly on predicting detailed traffic information for the US ATS. Initially, a 2-stage log-log model is applied to establish the significance of different inputs and to identify issues of endogeneity and multi-colinearity, while maintaining the simplicity of current models. Although the model shows high goodness of fit, it tested positive for both mentioned issues as well as presenting problems with causality. With the objective of solving these issues, a 3-stage model that is under development is introduced. this model employs logistic regression and discrete choice modelling. As part of future work, machine learning techniques such as clustering and neural networks will be applied to improve this model’s performance. © 2015, American Institute of Aeronautics and Astronautics Inc.

关键词： Data mining

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