Search Results - (((((((kent OR antiek) OR wiant) OR kantor) OR cantor) OR anne) OR walted) OR wanting) algorithms.

Comprehensive Ruby Programming. by Hudgens, Jordan

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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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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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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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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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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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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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Anesthesia student survival guide : a case-based approach

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Hands-On Reinforcement Learning with Python : Master Reinforcement and Deep Reinforcement Learning Using OpenAI Gym and TensorFlow. by Ravichandiran, Sudharsan

Table of Contents: “…Solving the taxi problem using Q learningSARSA; Solving the taxi problem using SARSA; The difference between Q learning and SARSA; Summary; Questions; Further reading; Chapter 6: Multi-Armed Bandit Problem; The MAB problem; The epsilon-greedy policy; The softmax exploration algorithm; The upper confidence bound algorithm; The Thompson sampling algorithm; Applications of MAB; Identifying the right advertisement banner using MAB; Contextual bandits; Summary; Questions; Further reading; Chapter 7: Deep Learning Fundamentals; Artificial neurons; ANNs; Input layer; Hidden layer; Output layer.…”
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Smart buildings, smart communities and demand response

Table of Contents: “…Demand Response in Smart Zero Energy Buildings and Grids / Nikos Kampelis -- DR in Smart and Near-zero Energy Buildings: The Leaf Community / Nikos Kampelis, Konstantinos Gobakis, Vagias Vagias, Denia Kolokotsa, Laura Standardi, Daniela Isidori, Cristina Cristalli, Fabio Maria Montagnino, Filippo Paredes, Pietro Muratore, Luca Venezia, Marina Kyprianou Dracou, Alaric Montenon, Andri Pyrgou, Theoni Karlessi, Mattheos Santamouris -- Performance of Industrial and Residential Near-zero Energy Buildings / Nikos Kampelis, Konstantinos Gobakis, Vagias Vagias, Denia Kolokotsa, Laura Standardi, Daniela Isidori, Cristina Cristalli, Fabio Maria Montagnino, Filippo Paredes, Pietro Muratore, Luca Venezia, Marina Kyprianou Dracou, Alaric Montenon, Andri Pyrgou, Theoni Karlessi, Mattheos Santamouris -- HVAC Optimization Genetic Algorithm for Industrial Near-Zero Energy Building Demand Response / Nikos Kampelis, Nikolaos Sifakis, Denia Kolokotsa, Konstantinos Gobakis, Konstantinos Kalaitzakis, Daniela Isidori, Cristina Cristalli -- Smart Grid/Community Load Shifting GA Optimization Based on Day-ahead ANN Power Predictions / Nikos Kampelis, Elisavet Tsekeri, Denia Kolokotsa, Konstantinos Kalaitzakis, Daniela Isidori, Cristina Cristalli -- Conclusions and Recommendations.…”
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Machine learning with R : learn how to use R to apply powerful machine learning methods and gain an insight into real-world applications by Lantz, Brett

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Predictive Modeling of Pharmaceutical Unit Operations. by Pandey, Preetanshu

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Artificial Neural Network Applications for Software Reliability Prediction. by Bisi, Manjubala

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Artificial intelligent techniques for electric and hybrid electric vehicles

Table of Contents: “…2.6 PID Controller -- 2.7 Fuzzy Control -- 2.8 Auto-Tuning Type Fuzzy PID Controller -- 2.9 Genetic Algorithm -- 2.10 Artificial Neural Network-Based Controller -- 2.11 BLDC Motor Speed Controller With ANN-Based PID Controller -- 2.11.1 PID Controller-Based on Neuro Action -- 2.11.2 ANN-Based on PID Controller -- 2.12 Analysis of Different Speed Controllers -- 2.13 Conclusion -- References -- Chapter 3 Optimization Techniques Used in Active Magnetic Bearing System for Electric Vehicles -- 3.1 Introduction -- 3.2 Basic Components of an Active Magnetic Bearing (AMB) -- 3.2.1 Electromagnet Actuator…”
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Fast sequential Monte Carlo methods for counting and optimization by Rubinstein, Reuven Y.

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Scala for Machine Learning - Second Edition. by Nicolas, Patrick R.

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Numerical linear algebra with applications : using MATLAB by Ford, William H.

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Numerical models for submerged breakwaters : coastal hydrodynamics and morphodynamics by Ahmadian, Amir Sharif

Table of Contents: “…3 Literature Review and BackgroundReferences; 4 Theories and Methodologies; 4.1 Introduction; 4.2 Traditional Models for Water Waves; 4.3 New Approaches; 4.3.1 Meshless Methods; 4.3.2 Artificial Intelligence Methods; MLP Networks; Back-Propagation Algorithm; Levenberg-Marquardt Algorithm; RBF Networks; References; 5 Mathematical Modeling and Algorithm Development; 5.1 Navier-Stokes Equations; 5.2 The Turbulent Model; 5.3 Initial and Boundary Conditions; 5.4 Shallow Waters; 5.5 The Extended Mild-Slope Equation; 5.6 Boussinesq Equations; 5.7 Smoothed Particles Hydrodynamics.…”
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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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