Search Results - (((((((ant OR kwants) OR wants) OR markant) OR cantor) OR anne) OR shared) OR hints) algorithms.

Advanced deep learning with R : become an expert at designing, building, and improving advanced neural network models using R by Rai, Bharatendra K.

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Power and energy systems III : selected, peer reviewed papers from the 2013 3rd International Conference on Power and Energy Systems (ICPES 2013), November 23-24, Bangkok, Thailand

Table of Contents: “…Appropriate Electric Energy Conservation Measures for Big Mosques in Riyadh CityBayesian Algorithm Based on Airborne Power Supply System; Study on the Cooling System of Super-Capacitors for Hybrid Electric Vehicle; A Charging Management of Electric Vehicles Based on Campus Survey Data; Back-EMF Position Detection Technology for Brushless DC Motor; Stress State of Turbine Blade Root and Rim Considering Manufacturing Variations; Analysis on a Gas Turbine Sealing Disk Structure and Material Strength; A Kind of Adjustable Electric Heating Pipe Power Electrode Preparation Equipment.…”
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MATLAB for Machine Learning. by Ciaburro, Giuseppe

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Frontiers In The Study Of Chaotic Dynamical Systems With Open Problems.

Table of Contents: “…Preface; Contents; Chapter 1 Problems with Lorenz's Modeling and the Algorithm of Chaos Doctrine; 1.1. Introduction; 1.2. …”
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Smart data pricing

Table of Contents: “…6.6 Day-Ahead Dynamic TDP6.7 Perspectives of Internet Ecosystem Stakeholders -- 6.8 Lessons From Day-Ahead Dynamic TDP Field Trials -- 6.9 Discussions And Conclusions -- Acknowledgments -- References -- III: Usage-Based Pricing -- Chapter 7: Quantifying the Costs of Customers for Usage-Based Pricing -- 7.1 Introduction -- 7.2 The Cost of a Customer in a Network -- 7.3 Discrepancy, The Metric of Comparing Different Cost-Sharing Policies -- 7.4 How Do We Compute the Costs of the Customers? …”
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Collaborative Annotation for Reliable Natural Language Processing: Technical and Sociological Aspects by Fort, Karen

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Mathematical Methods in Interdisciplinary Sciences. by Chakraverty, Snehashish

Table of Contents: “…1.2.2.1 Architecture of Single-Layer LgNN Model -- 1.2.2.2 Training Algorithm of Laguerre Neural Network (LgNN) -- 1.2.2.3 Gradient Computation of LgNN -- 1.3 Methodology for Solving a System of Fredholm Integral Equations of Second Kind -- 1.3.1 Algorithm -- 1.4 Numerical Examples and Discussion -- 1.4.1 Differential Equations and Applications -- 1.4.2 Integral Equations -- 1.5 Conclusion -- References -- Chapter 2 Deep Learning in Population Genetics: Prediction and Explanation of Selection of a Population -- 2.1 Introduction -- 2.2 Literature Review -- 2.3 Dataset Description…”
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Heterogeneous networks in LTE-Advanced by Acharya, Joydeep

Table of Contents: “…Chapter 3 LTE Signal Structure and Physical Channels 3.1 Introduction; 3.2 LTE Signal Structure; 3.3 Introduction to LTE Physical Channels and Reference Signals; 3.4 Resource Block Assignment; 3.5 Downlink Physical Channels; 3.5.1 Physical Broadcast Channel (PBCH); 3.5.2 Physical Downlink Shared Channel (PDSCH); 3.5.3 Physical Multicast Channel (PMCH); 3.5.4 Physical Control Format Indicator Channel (PCFICH); 3.5.5 Physical Hybrid ARQ Indicator Channel (PHICH); 3.5.6 Physical Downlink Control Channel (PDCCH); 3.6 Uplink Physical Channels; 3.6.1 Physical Uplink Shared Channel (PUSCH).…”
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Machine Learning for Asset Management New Developments and Financial Applications

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Blockchain and the Digital Economy : The Socio-Economic Impact of Blockchain Technology. by Steinmetz, Fred

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Arithmetic, Geometry, Cryptography and Coding Theory. by Bassa, Alp

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Ranking the Liveability of the World's Major Cities : the Global Liveable Cities Index (GLCI). by Tan, Khee Giap

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Choice modelling : the state-of-the-art and the state-of-practice : proceedings from the inaugural International Choice Modelling Conference

Table of Contents: “…On estimation of hybrid choice models / Denis Bolduc, Ricardo Alvarez-Daziano -- A model of travel happiness and mode switching / Maya Abou-Zeid, Moshe Ben-Akiva -- On path generation algorithms for route choice models / Emma Frejinger, Michel Bierlaire -- Mode choice endogeneity in value of travel time estimation / Stefan L. …”
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FX barrier options : a comprehensive guide for industry quants by Dadachanji, Zareer

Table of Contents: “…Stupid; 4.10 Five things we want from a model; 4.11 Stochastic volatility (SV) models; 4.11.1 SABR model; 4.11.2 Heston model; 4.12 Mixed local/stochastic volatility (lsv) models; 4.12.1 Term structure of volatility of volatility; 4.13 Other models and methods; 4.13.1 Uncertain Volatility (UV) models; 4.13.2 Jump-diffusion models; 4.13.3 Vanna-volga methods; 5 Smile Risk Management; 5.1 Black-Scholes with term structure; 5.2 Local volatility model; 5.3 Spot risk under smile models; 5.4 Theta risk under smile models; 5.5 Mixed local/stochastic volatility models; 5.6 Static hedging; 5.7 Managing risk across businesses; 6 Numerical Methods; 6.1 Finite-difference (FD) methods; 6.1.1 Grid geometry; 6.1.2 Finite-difference schemes; 6.2 Monte Carlo (MC) methods; 6.2.1 Monte Carlo schedules; 6.2.2 Monte Carlo algorithms; 6.2.3 Variance reduction; 6.2.4 The Brownian Bridge; 6.2.5 Early…”
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Model Building in Mathematical Programming. by Williams, H. Paul

Table of Contents: “…Intro -- Title Page -- Copyright -- Dedication -- Preface -- Preface to the Fifth Edition -- Part I -- Chapter 1: Introduction -- 1.1 The concept of a model -- 1.2 Mathematical programming models -- Chapter 2: Solving mathematical programming models -- 2.1 Algorithms and packages -- 2.2 Practical considerations -- 2.3 Decision support and expert systems -- 2.4 Constraint programming (CP) -- Chapter 3: Building linear programming models -- 3.1 The importance of linearity -- 3.2 Defining objectives -- 3.3 Defining constraints -- 3.4 How to build a good model…”
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Biological computation by Lamm, Ehud

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A Primer on Machine Learning Applications in Civil Engineering by Deka, Paresh Chandra

Table of Contents: “…Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Acknowledgments -- A Primer on Machine Learning Applications in Civil Engineering -- Author -- 1: Introduction -- 1.1 Machine Learning -- 1.2 Learning from Data -- 1.3 Research in Machine Learning: Recent Progress -- 1.4 Artificial Neural Networks -- 1.5 Fuzzy Logic (FL) -- 1.6 Genetic Algorithms -- 1.7 Support Vector Machine (SVM) -- 1.8 Hybrid Approach (HA) -- Bibliography -- 2: Artificial Neural Networks -- 2.1 Introduction to Fundamental Concepts and Terminologies -- 2.2 Evolution of Neural Networks -- 2.3 Models of ANN -- 2.4 McCulloch-Pitts Model -- 2.5 Hebb Network -- 2.6 Summary -- 2.7 Supervised Learning Network -- 2.7.1 Perceptron Network -- 2.7.2 Adaptive Linear Neuron -- 2.7.3 Back-Propagation Network -- 2.7.4 Radial Basis Function Network -- 2.7.5 Generalized Regression Neural Networks -- 2.7.6 Summary -- 2.8 Unsupervised Learning Networks -- 2.8.1 Introduction -- 2.8.2 Kohonen Self-Organizing Feature Maps -- 2.8.3 Counter Propagation Network -- 2.8.4 Adaptive Resonance Theory Network -- 2.8.5 Summary -- 2.9 Special Networks -- 2.9.1 Introduction -- 2.9.2 Gaussian Machine -- 2.9.3 Cauchy Machine -- 2.9.4 Probabilistic Neural Network -- 2.9.5 Cascade Correlation Neural Network -- 2.9.6 Cognitive Network -- 2.9.7 Cellular Neural Network -- 2.9.8 Optical Neural Network -- 2.9.9 Summary -- 2.10 Working Principle of ANN -- 2.10.1 Introduction -- 2.10.2 Types of Activation Function -- 2.10.3 ANN Architecture -- 2.10.4 Learning Process -- 2.10.5 Feed-Forward Back Propagation -- 2.10.6 Strengths of ANN -- 2.10.7 Weaknesses of ANN -- 2.10.8 Working of the Network -- 2.10.9 Summary -- Bibliography -- 3: Fuzzy Logic -- 3.1 Introduction to Classical Sets and Fuzzy Sets -- 3.1.1 Classical Sets -- 3.1.2 Fuzzy Sets -- 3.1.3 Summary.…”
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New Horizons in Mobile and Wireless Communications, Volume 1 : Radio Interfaces. by Prasad, Ramjee

Table of Contents: “…1.3 Research and Standardization Activities Toward New Radio Interfaces1.3.1 European-Funded Research Activities; 1.3.2 Other Activities; 1.4 Preview of the Book; References; Chapter 2 Spectrum-Efficient Radio Interface Technologies; 2.1 Introduction; 2.1.1 Radio Interfaces for Ubiquitous Communications; 2.1.2 OFDM-Based Radio Interfaces in the Scope of Next Generation Systems; 2.1.3 Coexistence and Spectrum Sharing; 2.1.4 Opportunities for Secondary Spectrum Use; 2.1.5 Multiband Transmissions; 2.2 Radio Interfaces Optimized for PANs; 2.2.1 Scenarios and Radio Propagation Models for PANs.…”
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Uncommon sense : investment wisdom since the stock market's dawn by Kemp, Michael E.

Table of Contents: “…-- RELATING BOOK VALUE PER SHARE TO MARKET PRICE -- WHAT IS A LOW P/B RATIO TELLING US? …”
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Microwave and millimeter wave circuits and systems : emerging design, technologies, and applications

Table of Contents: “…1.1.7 MBF Model -- the Memoryless PA Behavioural Model of ChoiceAcknowledgements; References; 2 Artificial Neural Network in Microwave Cavity Filter Tuning; 2.1 Introduction; 2.2 Artificial Neural Networks Filter Tuning; 2.2.1 The Inverse Model of the Filter; 2.2.2 Sequential Method; 2.2.3 Parallel Method; 2.2.4 Discussion on the ANN's Input Data; 2.3 Practical Implementation -- Tuning Experiments; 2.3.1 Sequential Method; 2.3.2 Parallel Method; 2.4 Influence of the Filter Characteristic Domain on Algorithm Efficiency; 2.5 Robots in the Microwave Filter Tuning; 2.6 Conclusions; Acknowledgement…”
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