Search Results - (((((((ant OR wantinga) OR semantic) OR want) OR cantor) OR anne) OR slave) OR mantis) algorithms.

Advances in time series forecasting. Volume 2

Table of Contents: “…INTRODUCTION -- CLASSICAL TIME SERIES FORECASTING MODELS -- ARTIFICIAL NEURAL NETWORKS FOR FORECASTING TIME SERIES -- A NEW ARTIFICIAL NEURAL NETWORK WITH DETERMINISTIC COMPONENTS -- APPLICATIONS -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A Fuzzy Time Series Approach Based on Genetic Algorithm with Single Analysis Process -- Ozge Cagcag Yolcu* -- INTRODUCTION -- FUZZY TIME SERIES -- RELATED METHODS -- Genetic Algorithm (GA) -- Single Multiplicative Neuron Model -- PROPOSED METHOD -- APPLICATIONS -- CONCLUSION AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Forecasting Stock Exchanges with Fuzzy Time Series Approach Based on Markov Chain Transition Matrix -- Cagdas Hakan Aladag1,* and Hilal Guney2 -- INTRODUCTION -- FUZZY TIME SERIES -- TSAUR 'S FUZZY TIME SERIES MARKOV CHAIN MODEL -- THE IMPLEMENTATION -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A New High Order Multivariate Fuzzy Time Series Forecasting Model -- Ufuk Yolcu* -- INTRODUCTION -- RELATED METHODOLOGY -- The Fuzzy C-Means (FCM) Clustering Method -- Single Multiplicative Neuron Model Artificial Neural Network (SMN-ANN) -- Fuzzy Time Series -- THE PROPOSED METHOD -- APPLICATIONS -- CONCLUSIONS AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Fuzzy Functions Approach for Time Series Forecasting -- Ali Z. …”
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Automatic Text Summarization by Torres-Moreno, Juan-Manuel

Table of Contents: “…State-of-the-art approaches; 3.4. Latent semantic analysis; 3.5. Graph-based approaches; 3.6. …”
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PRINCIPLES OF QUANTUM ARTIFICIAL INTELLIGENCE. by Wichert, Andreas

Table of Contents: “…Computation; 2.1 Entscheidungsproblem; 2.1.1 Cantor's diagonal argument; 2.1.2 Reductio ad absurdum; 2.2 Complexity Theory; 2.2.1 Decision problems; 2.2.2 P and NP; 2.3 Church-Turing Thesis; 2.3.1 Church-Turing-Deutsch principle; 2.4 Computers; 2.4.1 Analog computers; 2.4.2 Digital computers; 2.4.3 Von Neumann architecture; 3. …”
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Creating wicked students : designing courses for a complex world by Hanstedt, Paul, 1965-

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Aggregating Dialectology, Typology, and Register Analysis : Linguistic Variation in Text and Speech

Table of Contents: “…Kretzschmar -- A weakly supervised multivariate approach to the study of language variation / Sascha Diwersy, Stefan Evert, and Stella Neumann -- Semantic weighting mechanisms in scalable lexical sociolectometry / Tom Ruette, Dirk Geeraerts, Yves Peirsman and Dirk Speelman -- Temperature in the word space : Sense exploration of temperature expressions using word-space modelling / Maria Koptjevskaja-Tamm and Magnus Sahlgren -- The perfect map : Investigating the cross-linguistic distribution of TAME categories in a parallel corpus / Östen Dahl -- Explorations into variation across Slavic : Taking a bottom-up approach / Ruprecht von Waldenfels -- Where Alice fell into : Motion events from a parallel corpus / Annemarie Verkerk -- Algorithmic typology and going from known to similar unknown categories within and across languages / Bernhard Wälchli -- Inducing place distinctions of consonants from their distribution in words / Thomas Mayer -- Laws of language and text in quantitative and synergetic linguistics / Reinhard Köhler.…”
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Pulmonary arterial hypertension : diagnosis and evidence-based treatment

Table of Contents: “…Combination therapy in pulmonary arterial hypertension / Anne Keogh and Marius Hoeper -- Interventional and surgical modalities of treatment for pulmonary arterial hypertension / Julio Sandoval and Ramona Doyle -- End points and clinical trial design in pulmonary arterial hypertension : clinical and regulatory perspectives / Andrew J. …”
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Machine Learning with Swift : Artificial Intelligence for iOS. by Sosnovshchenko, Oleksandr

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Pattern Recognition in Computational Molecular Biology : Techniques and Approaches by Elloumi, Mourad, Iliopoulos, Costas, Wang, Jason T. L., Zomaya, Albert Y.

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Verification of communication protocols in web services : model-checking service compositions by Mukherjee, Anshuman

Table of Contents: “…8.2 Overview of the Problem and Solution8.3 Related Work; 8.4 Colored Petri Net Semantics for BPEL; 8.4.1 Component A; 8.4.2 Component B; 8.4.3 Object Model for BPEL Activities; 8.4.4 XML Templates; 8.4.5 Algorithm for Cloning Templates; 8.5 Results; 8.6 Discussion; 8.7 Summary; References; 9 CONCLUSIONS AND OUTLOOK; 9.1 Results; 9.2 Discussion; 9.3 What Could Be Improved?…”
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Handbook of power systems. II

Table of Contents: “…Cover -- Handbook of Power Systems II13; -- Preface of Volume II13; -- Contents of Volume II13; -- Contents13; of Volume I -- Contributors13; -- Part I Transmission and Distribution Modeling -- Recent Developments in Optimal Power Flow Modeling Techniques -- 1 Introduction -- 2 Physical Network Representation -- 3 Operational Constraints -- 4 Tap-Changing and Regulating Transformers -- 5 FACTS Devices -- 6 OPF Objective Functions and Formulations -- 7 OPF Solution Techniques -- 8 Numerical Examples -- 9 Conclusion -- References -- Algorithms for Finding Optimal Flows in Dynamic Networks -- 1 Optimal Dynamic Network Flow Models and Power Industry -- 2 Minimum Cost Dynamic Single: Commodity Flow Problems and Algorithms for Their Solving -- 3 Minimum Cost Dynamic Multicommodity Flow Problems and Algorithms for Their Solving -- References -- Signal Processing for Improving Power Quality -- 1 Wavelet-based Algorithm for Harmonics Analysis -- 2 Wavelet-based Algorithm for Nonstationary Power System Waveform Analysis -- 3 Wavelet-GA-ANN Based Hybrid Model for Accurate Prediction of Short-term Load Forecast -- 4 Conclusions -- References -- Transmission Valuation Analysis based on Real Options with Price Spikes -- 1 Introduction -- 2 Behavior of Commodity Prices -- 3 Valuation of Obligations and Options -- 4 Valuation in the Presence of Spikes -- 5 Conclusions -- References -- Part II Forecasting in Energy -- Short-term Forecasting in Power Systems: A Guided Tour -- 1 Introduction -- 2 Electricity Load Forecasting -- 3 Wind Power Forecasting -- 4 Forecasting Electricity Prices -- 5 Conclusions -- References -- State-of-the-Art of Electricity Price Forecasting in a Grid Environment -- 1 Introduction -- 2 State-of-the-Art Techniques of Electricity Price Forecasting -- 3 Input8211;Output Specifications of Electricity Price Forecasting Techniques -- 4 Comparing Existing Statistical Techniques for Electricity Price Forecasting -- 5 Implementations of Electricity Price Forecasting in a Grid Environment -- 6 Conclusions -- References -- Modelling the Structure of Long-Term Electricity Forward Prices at Nord Pool -- 1 Introduction -- 2 Long-term Forward Price Process -- 3 Model Estimation -- 4 Conclusions -- References -- Hybrid Bottom-Up/Top-Down Modeling of Prices in Deregulated Wholesale Power Markets -- 1 Introduction -- 2 Top-Down Models for Electricity Price Forecasting -- 3 Hybrid Bottom-Up/Top-Down Modeling -- 4 A Hybrid Model for the New Zealand Electricity Market -- 5 A Hybrid Model for the Australian Electricity Market -- 6 Conclusions -- References -- Part III Energy Auctions and Markets -- Agent-based Modeling and Simulation of Competitive Wholesale Electricity Markets -- 1 Introduction -- 2 Agent-based Modeling and Simulation -- 3 Behavioral Modeling -- 4 Market Modeling -- 5 Conclusions -- References -- Futures Market Trading for Electricity Producers and Retailers -- 1 Introduction: Futures Market Trading -- 2 Producer Trading -- 3 Retailer Trading -- 4 Conclusions -- References -- A Decision Support System for Generation Planning and Operation in Electricity Markets -- 1 Introduction -- 2 Long-term Stochastic Market Planning Model -- 3 Medium-term Stochastic Hydrothermal Coordination Model -- 4 Medium-term Stochastic Simulation Model -- T$29828.…”
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There's Something about Gödel : The Complete Guide to the Incompleteness Theorem. by Berto, Francesco

Table of Contents: “…. -- 6 ... and the unsatisfied logicists, Frege and Russell -- 7 Bits of set theory -- 8 The Abstraction Principle -- 9 Bytes of set theory -- 10 Properties, relations, functions, that is, sets again -- 11 Calculating, computing, enumerating, that is, the notion of algorithm…”
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Visible Business : Uncover the Blindspots and Engage the World's Female Economy. by Brideson, RJ

Table of Contents: “…Blind Spots; Contents; Foreword; About the Author; Acknowledgements; To my community; To my village; Preface; Introduction; Chapter 1 From history to herstory; The birth of business marketing; Things have changed -- or have they?; Women want more; The wo-man algorithm; Become conscious of the bias; From reject to results; Chapter 2 Are you blind?…”
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Cognitive Electronic Warfare : An Artificial Intelligence Approach. by Haigh, Karen

Table of Contents: “…-- 1.5 Reader's Guide -- 1.6 Conclusion -- References -- 2 Objective Function -- 2.1 Observables That Describe the Environment -- 2.1.1 Clustering Environments -- 2.2 Control Parameters to Change Behavior -- 2.3 Metrics to Evaluate Performance -- 2.4 Creating a Utility Function -- 2.5 Utility Function Design Considerations -- 2.6 Conclusion -- References -- 3 ML Primer -- 3.1 Common ML Algorithms -- 3.1.1 SVMs -- 3.1.2 ANNs -- 3.2 Ensemble Methods -- 3.3 Hybrid ML -- 3.4 Open-Set Classification -- 3.5 Generalization and Meta-learning -- 3.6 Algorithmic Trade-Offs -- 3.7 Conclusion -- References -- 4 Electronic Support -- 4.1 Emitter Classification and Characterization -- 4.1.1 Feature Engineering and Behavior Characterization -- 4.1.2 Waveform Classification -- 4.1.3 SEI -- 4.2 Performance Estimation -- 4.3 Multi-Intelligence Data Fusion -- 4.3.1 Data Fusion Approaches -- 4.3.2 Example: 5G Multi-INT Data Fusion for Localization -- 4.3.3 Distributed-Data Fusion -- 4.4 Anomaly Detection -- 4.5 Causal Relationships -- 4.6 Intent Recognition -- 4.6.1 Automatic Target Recognition and Tracking -- 4.7 Conclusion -- References -- 5 EP and EA -- 5.1 Optimization -- 5.1.1 Multi-Objective Optimization -- 5.1.2 Searching Through the Performance Landscape -- 5.1.3 Optimization Metalearning -- 5.2 Scheduling -- 5.3 Anytime Algorithms -- 5.4 Distributed Optimization -- 5.5 Conclusion.…”
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Three Views of Logic : Mathematics, Philosophy, and Computer Science. by Loveland, Donald W.

Table of Contents: “…Proof Theory; 1 Propositional Logic; 1.1 Propositional Logic Semantics; 1.2 Syntax: Deductive Logics; 1.3 The Resolution Formal Logic; 1.4 Handling Arbitrary Propositional Wffs; 2 Predicate Logic; 2.1 First-Order Semantics; 2.2 Resolution for the Predicate Calculus; 2.2.1 Substitution; 2.2.2 The Formal System for Predicate Logic; 2.2.3 Handling Arbitrary Predicate Wffs; 3 An Application: Linear Resolution and Prolog; 3.1 OSL-Resolution; 3.2 Horn Logic; 3.3 Input Resolution and Prolog; Appendix A: The Induction Principle.…”
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Architecture-aware optimization strategies in real-time image processing by Li, Chao, Balla-Arabe, Souleymane, Yang, Fan

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Big data in medical science and healthcare management : diagnosis, therapy, side effects

Table of Contents: “…Autopilot and "doctor algorithm"? -- 1. Intro big data for healthcare? / Peter Langkafel -- 2. …”
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Real-time database systems : architecture and techniques

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Gradience in grammar : generative perspectives

Table of Contents: “…Frisch and Adrienne Stearns -- Intermediate syntactic variants in a dialect : standard speech repertoire and relative acceptability / Leonie Cornips -- Gradedness and optionality in mature and developing grammars / Antonella Sorace -- Decomposing gradience : quantitative versus qualitative distinctions / Matthias Schlesewsky, Ina Bornkessel, and Brian McElree -- Gradient perception of intonation / Caroline Féry and Ruben Stoel -- Prototypicality judgements as inverted perception / Paul Boersma -- Modelling productivity with the gradual learning algorithm : the problem of accidentally exceptionless generalizations / Adam Albright and Bruce Hayes -- Gradedness as relative efficiency in the processing of syntax and semantics / John A. …”
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Numerical Methods in Contact Mechanics. by Yastrebov, Vladislav A.

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Machine Learning for Asset Management New Developments and Financial Applications

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