Search Results - empirical (algorithmes OR algorithm)

Intensity Modulated Radiation Therapy : A Clinical Overview. by Das, Indra J.

Table of Contents: “…9.3 The optimization objectives -- 9.4 The optimization algorithms -- 9.4.1 The deterministic algorithms -- 9.4.2 The stochastic algorithms -- 9.5 The direct aperture optimization -- 9.6 The biological optimization -- 9.6.1 The radiobiological models for TCP, NTCP, EUD -- 9.7 Benefit and deficiencies in biological optimization -- 9.8 Robust optimization -- References -- Chapter 10 Dose calculation -- 10.1 Required accuracy in dose calculation -- 10.2 Dose calculation algorithms and classification -- 10.2.1 The empirical models -- 10.2.2 The semi-empirical, correction-based algorithms…”
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Handbook of Mathematical Induction. by Gunderson, David S.

Table of Contents: “…Chapter 14: Logic and languageChapter 15: Graphs; Chapter 16: Recursion and algorithms; Chapter 17: Games and recreations; Chapter 18: Relations and functions; Chapter 19: Linear and abstract algebra; Chapter 20: Geometry; Chapter 21: Ramsey theory; Chapter 22: Probability and statistics; Part III: Solutions and hints to exercises; Chapter 23: Solutions: Foundations; Chapter 24: Solutions: Inductive techniques applied to the infinite; Chapter 25: Solutions: Paradoxes and sophisms; Chapter 26: Solutions: Empirical induction; Chapter 27: Solutions: Identities.…”
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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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Modelling forest systems

Table of Contents: “…Colour Plates; Principal Contributors; Preface; Part 1 Forest Reality and Modelling Strategies; 1 Suggestions for Choosing an Appropriate Level for Modelling Forest Stands; 2 Mapping Lodgepole Pine Site Index in Alberta; 3 Growth Modelling of Eucalyptus regnans for Carbon Accounting at the Landscape Scale; 4 Spatial Distribution Modelling of Forest Attributes Coupling Remotely Sensed Imagery and GIS Techniques; 5 Algorithmic and Interactive Approaches to Stand Growth Modelling; 6 Linking Process-based and Empirical Forest Models in Eucalyptus Plantations in Brazil.…”
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Intelligent materials, applied mechanics and design science : selected, peer reviewed papers from the 2011 international conference on intelligent materials, applied mechanics and...

Table of Contents: “…Intelligent Materials, Applied Mechanics and Design Science; Preface and Committee; Table of Contents; Chapter 1: Intelligent Materials, Energy Science and Dynamic System; Gear Fault Diagnoise Based on Ensemble Empirical Mode Decomposition and Instantaneous Energy Density Spectrum; Numerical Analysis of Nonlinear Behaviors of a Flexible Rotor Dynamic System with Turbulent Journal Bearings Support; Dynamic Path Planning Algorithm Based on Chaos Genetic Vehicle Navigation; The Hybrid Genetic Algorithm of Single-Machine Materials Manufacturing Process with Periodic Maintenance.…”
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Volatility Surface and Term Structure : High-profit Options Trading Strategies. by Lai, Kin Keung

Table of Contents: “…Cover; Title; Copyright; Contents; List of figures; List of tables; Preface; 1 Introduction; 1.1 Implied volatility; 1.2 Local volatility model; 1.3 Stochastic volatility model; 2 A novel model-free term structure for stock prediction; 2.1 Introduction; 2.2 Volatility model; 2.3 Model-free term structure; 2.4 Empirical tests; 2.5 Conclusions; 3 An adaptive correlation Heston model for stock prediction; 3.1 Introduction; 3.2 Adaptive correlation coefficient model; 3.3 Empirical tests; 3.4 Conclusions; 4 The algorithm to control risk using options; 4.1 Introduction.…”
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Quantifying human resources : uses and analyses by Coron, Clotilde

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Wireless technologies in intelligent transportation systems

Table of Contents: “…Adaptive Beamforming Algorithms; 4.e.1. Sample Matrix Inversion (SMI) Algorithm; 4.e.2. …”
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Systemic Risk from Global Financial Derivatives. by Markose, Sheri M.

Table of Contents: “…Empirical (Small World) Core-Periphery Network Algorithm; 4. …”
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Wireless communications systems design by Kim, Haesik

Table of Contents: “…6.1.2 Example of Turbo Encoding and Decoding6.1.3 Hardware Implementation of Turbo Encoding and Decoding; 6.2 Turbo Product Codes; 6.2.1 Turbo Product Encoding and Decoding Algorithm; 6.2.2 Example of Turbo Product Encoding and Decoding; 6.2.3 Hardware Implementation of Turbo Product Encoding and Decoding; 6.3 Low-Density Parity Check Codes; 6.3.1 LDPC Encoding and Decoding Algorithms; 6.3.2 Example of LDPC Encoding and Decoding; 6.3.3 Hardware Implementation of LDPC Encoding and Decoding; 6.4 Problems; References; Chapter 7 Orthogonal Frequency-Division Multiplexing; 7.1 OFDM System Design.…”
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Statistical analysis techniques in particle physics : fits, density estimation and supervised learning by Narsky, Ilya, Porter, Frank Clifford

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The importance of health informatics in public health during a pandemic

Table of Contents: “…Confirmatory Factors to Nursing Practice for Patient Safety of Nurses in Kalasin Hospital, Kalasin Province, Thailand -- Patient Awareness of the Severity of Their Information and Medication Management-Related Adverse Events -- The Quality Improvement Information System for Surveillance and Monitoring for Patient Safety and Personal Safety in Kalasin Hospital, Kalasin Province, Thailand -- Iconic Visualization of Sickle Cell Patients Current and Past Health Status -- Using Machine Learning Algorithms to Predict Antimicrobial Resistance and Assist Empirical Treatment…”
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Multivariate statistics : proceedings of the 6th Tartu Conference, Tartu, Estonia, 19-22 August 1999

Table of Contents: “…s F-statistic: A simulation studyZero-boundary Voronoi partitions -- On expected values of fourth-degree matrix products of a multinormal matrix variate -- A multivariate Buckley-James estimator -- A new algorithm of the linear discriminant function using integer programming -- Robustification of “approximating approachâ€? …”
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Machine Learning for Financial Engineering. by Gyorfi, Laszlo

Table of Contents: “…Experiments on Heuristic Algorithms3.4. Growth-Optimal Portfolio Selection Algorithms; 3.5. …”
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Computer-Aided Learning and Analysis for COVID-19 Disease. by Dhiman, Gaurav

Table of Contents: “…Cover -- Special issue (part 1) on computer-aided learning and analysis for COVID-19 disease -- COVID-19: risk prediction through nature inspired algorithm -- E-biomedical: a positive prospect to monitor human healthcare system using blockchain technology -- Pattern analysis: predicting COVID-19 pandemic in India using AutoML -- Predicting future diseases based on existing health status using link prediction -- Detection of COVID-19 cases through X-ray images using hybrid deep neural network -- Time series analysis of COVID-19 cases…”
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Marvels of Artificial and Computational Intelligence in Life Sciences. by Sivaraman, Thirunavukkarasu

Table of Contents: “…Cover -- Title -- Copyright -- End User License Agreement -- Contents -- Foreword I -- Foreword II -- Preface -- List of Contributors -- Artificial Intelligence for Infectious Disease Surveillance -- Sathish Sankar1,*, Pitchaipillai Sankar Ganesh1 and Rajalakshmanan Eswaramoorthy2 -- INTRODUCTION -- CONCLUSION -- ACKNOWLEDGEMENT -- REFERENCES -- Recent Innovations in Artificial Intelligence (AI) Algorithms in Electrical and Electronic Engineering for Future Transformations…”
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Linkage Analysis and Gene Mapping. by WANG, Jiankang

Table of Contents: “…Theoretical Frequencies of 4 Homozygotes in Permanent Populations -- Genotypic Frequencies of Two Co-Dominant Loci in Temporary Populations -- Genotypic Frequencies of One Co-Dominant Locus and One Dominant Locus in Temporary Populations -- Genotypic Frequencies of One Co-Dominant Locus and One Recessive Locus in Temporary Populations -- Genotypic Frequencies of Two Dominant Loci in Temporary Populations -- Genotypic Frequencies of One Dominant Locus and One Recessive Locus in Temporary Populations -- Genotypic Frequencies of Two Recessive Loci in Temporary Populations -- Estimation of Two-Point Recombination Frequency -- Maximum Likelihood Estimation of Recombination Frequency in DH Populations -- General Procedure on the Maximum Likelihood Estimation of Recombination Frequency -- Estimation of Recombination Frequency Between One Co-Dominant and One Dominant Marker in F2 Population -- Initial Values in Newton Algorithm -- EM Algorithm in Estimating Recombination Frequency in F2 Populations -- Effects on the Estimation of Recombination Frequency from Segregation Distortion -- Exercises -- Three-Point Analysis and Linkage Map Construction -- Three-Point Analysis and Mapping Function -- Genetic Interference and Coefficient of Interference -- Mapping Function -- Construction of Genetic Linkage Maps -- Marker Grouping Algorithm -- Marker Ordering Algorithm -- Use of the k-Optimal Algorithm in Linkage Map Construction -- Rippling of the Ordered Markers -- Integration of Multiple Maps -- Comparison of the Recombination Frequency Estimation in Different Populations -- LOD Score in Testing the Linkage Relationship in Different Populations -- Accuracy of the Estimated Recombination Frequency -- Least Population Size to Declare the Significant Linkage Relationship and Close Linkage -- Linkage Analysis in Random Mating Populations.…”
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Missing Data Methods : Cross-Sectional Methods and Applications. by Drukker, David M.

Table of Contents: “…NotesAcknowledgment; References; Orthogonality in the single index model; On the estimation of selection models when participation is endogenous and misclassified; Introduction; The model and estimator; Sampling algorithm; Simulated data example; Summary and conclusions; Notes; Acknowledgments; References; summary tables for additional simulations; Process for simulating non -- normal errors; Efficient probit estimation with partially missing covariates; Introduction; Model Specification; Efficient estimators and variances; Testing assumptions and possible modifications; Other models.…”
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Machine Learning for Asset Management New Developments and Financial Applications

Table of Contents: “…A review of machine learning algorithms for prediction of market direction -- 2.3.1. …”
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Combinatorial Development Of Solid Catalytic Materials : Design Of High-Throughput Experiments, Data Analysis, Data Mining.

Table of Contents: “…Tuning Evolutionary Algorithms with Artificial Neural Networks (M. Holena) -- 7.1. …”
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