Search Results - (((((((ante OR want) OR mantis) OR when) OR cantor) OR anne) OR share) OR hints) algorithms.

Navigation signal processing for GNSS software receivers by Pany, Thomas

Full text (MFA users only)

Introduction to Mathematical Optimization : From Linear Programming to Metaheuristics. by Yang, Xin-She

Table of Contents: “…Tabu Search""; ""8.1 Tabu Search""; ""8.2 Travelling Salesman Problem""; ""8.3 Tabu Search for TSP""; ""9. Ant Colony Optimization""; ""9.1 Behaviour of Ants""; ""9.2 Ant Colony Optimization""; ""9.3 Double Bridge Problem""; ""9.4 Multi-Peak Functions""; ""10. …”
Full text (MFA users only)

Mastering machine learning with scikit-learn : learn to implement and evaluate machine learning solutions with scikit-learn by Hackeling, Gavin

Full text (MFA users only)

Machine learning : a Bayesian and optimization perspective by Theodoridis, Sergios, 1951-

Table of Contents: “…Probability and stochastic processes -- Learning in parametric modeling: basic concepts and directions -- Mean-square error linear estimation -- Stochastic gradient descent: the LMS algorithm -- The least-squares family -- Classification: a tour of the classics -- Parameter learning: a convex analytic path -- Sparsity-aware learning: concepts and theoretical foundations -- Sparcity-aware learning: algorithms and applications -- Learning in reproducing Kernel Hilbert spaces -- Bayesian learning: inference and the EM alogrithm -- Bayesian learning: approximate inference and nonparametric models -- Monte Carlo methods -- Probabilistic graphical models: Part I -- Probabilistic graphical models: Part II -- Particle filtering -- Neural networks and deep learning -- Dimensionality reduction -- Appendix A LInear algebra -- Appendix B Probability theory and statistics -- Appendix C Hints on constrained optimization.…”
Full text (MFA users only)

Visual Data Mining : The VisMiner Approach. by Anderson, Russell K.

Table of Contents: “…Regression Analysis -- The Regression Model -- Correlation and Causation -- Algorithms for Regression Analysis -- Assessing Regression Model Performance -- Model Validity -- Looking Beyond R2 -- Polynomial Regression -- Artificial Neural Networks for Regression Analysis -- Dataset Preparation -- Tutorial -- A Regression Model for Home Appraisal -- Modeling with the Right Set of Observations -- Exercise 6.1 -- ANN Modeling -- The Advantage of ANN Regression -- Top-Down Attribute Selection -- Issues in Model Interpretation -- Model Validation -- Model Application -- Summary…”
Full text (MFA users only)

Evolutionary Computing in Advanced Manufacturing. by Tiwari, Manoj

Table of Contents: “…Cover; Half Title page; Title page; Copyright page; Preface; List of Contributors; Chapter 1: Production Planning Using Genetic Algorithm; 1.1 Introduction; 1.2 Production Planning Models; 1.3 Genetic Algorithm; 1.4 Implementation of GA; 1.5 Summary; Further Reading; Chapter 2: Process Planning through Ant Colony Optimization; 2.1 Introduction; 2.2 Ant Colony Optimization (ACO); References; Chapter 3: Introducing a Hybrid Genetic Algorithm for Integration of Set Up and Process Planning; 3.1 Introduction; 3.2 Process Planning; 3.3 Machine Set-up Time; 3.4 Chromosome Representation.…”
Full text (MFA users only)

Modeling Reality : How Computers Mirror Life. by Białynicki-Birula, Iwo

Table of Contents: “…Contents; 1 From building blocks to computers: Models and modeling; 2 The game of life: A legendary cellular automaton; 3 Heads or tails: Probability of an event; 4 Galton's board: Probability and statistics; 5 Twenty questions: Probability and information; 6 Snowflakes: The evolution of dynamical systems; 7 The Lorenz butterfly: Deterministic chaos; 8 From Cantor to Mandelbrot: Self-similarity and fractals; 9 Typing monkeys: Statistical linguistics; 10 The bridges of Königsberg: Graph theory; 11 Prisoner's dilemma: Game theory; 12 Let the best man win: Genetic algorithms.…”
Full text (MFA users only)

Learning Boost C++ libraries : solve practical programming problems using powerful, portable, and expressive libraries from Boost by Mukherjee, Arindam

Table of Contents: “…Shared ownership semanticsboost::shared_ptr and std::shared_ptr; Intrusive smart pointers -- boost::intrusive_ptr; shared_array; Managing non-memory resources using smart pointers; Self-test questions; Summary; References; Chapter 4: Working with Strings; Text processing with Boost String Algorithms library; Using Boost String Algorithms; Find algorithms; Case-conversion and trimming algorithms; The replace and erase algorithms; The split and join algorithms; Splitting text using the Boost Tokenizer library; Tokenizing based on separators…”
Full text (MFA users only)

Autonomous mobile robots and multi-robot systems : motion-planning, communication, and swarming

Full text (MFA users only)

F♯ for Machine Learning Essentials. by Mukherjee, Sudipta

Full text (MFA users only)

OIPE 2012

Table of Contents: “…N-level output space mapping for electromagnetic design optimizationHigh-speed functionality optimization of five-phase PM machine using third harmonic current; Topology optimization of magnetostatic shielding using multistep evolutionary algorithms with additional searches in a restricted design space ; Adaptive unscented transform for uncertainty quantification in EMC large-scale systems; Ant colony optimization for the topological design of interior permanent magnet (IPM)machines; Multiobjective approach developed for optimizing the dynamic behavior of incremental linear actuators.…”
Full text (MFA users only)

Quantum Computation and Information. by Lomonaco, Samuel J.

Table of Contents: “…Vintage Simon quantum hidden subgroup algorithms (QHSAs)Part 5. Vintage Shor Algorithms -- 11. …”
Full text (MFA users only)

Development of Modern Statistics and Related Topics : In Celebration of Prof Yaoting Zhang's 70th Birthday. by Zhang, Heping

Table of Contents: “…Estimation When Variances Are Known ; 4. Estimation when variances are Unknown ; 5. …”
Full text (MFA users only)

Differential and Differential-Algebraic Systems for the Chemical Engineer : Solving Numerical Problems. by Buzzi-Ferraris, Guido

Table of Contents: “…1.10 Adaptive Methods1.10.1 Method Derived from the Gauss-Kronrod Algorithm; 1.10.2 Method Derived from the Extended Trapezoid Algorithm; 1.10.3 Method Derived from the Gauss-Lobatto Algorithm; 1.11 Parallel Computations; 1.12 Classes for Definite Integrals; 1.13 Case Study: Optimal Adiabatic Bed Reactors for Sulfur Dioxide with Cold Shot Cooling; 2 Ordinary Differential Equations Systems; 2.1 Introduction; 2.2 Algorithm Accuracy; 2.3 Equation and System Conditioning; 2.4 Algorithm Stability; 2.5 Stiff Systems; 2.6 Multistep and Multivalue Algorithms for Stiff Systems.…”
Full text (MFA users only)

Advances in Computational Intelligence : Theory & Applications by Wang, Fei-Yue

Table of Contents: “…Lin and F.-Y. Wang -- 8. Ant colony algorithms: the state-of-the-art / J. …”
Full text (MFA users only)

What intelligence tests miss : the psychology of rational thought by Stanovich, Keith E., 1950-

Table of Contents: “…Inside George W. Bush's mind : hints at what IQ tests miss -- Dysrationalia : separating rationality and intelligence -- The reflective mind, the algorithmic mind, and the autonomous mind -- Cutting intelligence down to size -- Why intelligent people doing foolish things is no surprise -- The cognitive miser : ways to avoid thinking -- Framing and the cognitive miser -- Myside processing : heads I win, tails I win too! …”
Full text (MFA users only)

Intelligent Technologies : From Theory to Applications - The New Trends in Computational Intelligence. by Kvasnicka, V.

Table of Contents: “…Neural Networks; Superconvergence Concept in Machine Learning; Application of the Parallel Population Learning Algorithm to Training Feed-forward ANN; Markovian Architectural Bias of Recurrent Neural Networks; SOFM Training Speedup; Generalized Forecasting Sigma-Pi Neural Network; Human Centered Intelligent Robots Using "Ontological Neural Network"; Trajectory Bounds of Solutions of Delayed Cellular Neural Networks Differential Systems; From Plain to Modular Topology: Automatic Modularization of Structured ANNs.…”
Full text (MFA users only)

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.…”
Full text (MFA users only)

Data Science : The Executive Summary - a Technical Book for Non-Technical Professionals. by Cady, Field

Table of Contents: “…Chapter 3 Working with Modern Data -- 3.1 Unstructured Data and Passive Collection -- 3.2 Data Types and Sources -- 3.3 Data Formats -- 3.3.1 CSV Files -- 3.3.2 JSON Files -- 3.3.3 XML and HTML -- 3.4 Databases -- 3.4.1 Relational Databases and Document Stores -- 3.4.2 Database Operations -- 3.5 Data Analytics Software Architectures -- 3.5.1 Shared Storage -- 3.5.2 Shared Relational Database -- 3.5.3 Document Store + Analytics RDB -- 3.5.4 Storage + Parallel Processing -- Chapter 4 Telling the Story, Summarizing Data -- 4.1 Choosing What to Measure…”
Full text (MFA users only)

Artificial intelligence : approaches, tools, and applications

Table of Contents: “…EVOLUTIONARY COMPUTING ; 2.1. Genetic Algorithms ; 2.2. Mechanism of a Genetic Algorithm ; 3. …”
Full text (MFA users only)