Search Results - (((((((ant OR find) OR cantee) OR wanting) OR cantor) OR anne) OR maarten) OR tkanto) algorithms.

The Complete Rust Programming Reference Guide : Design, Develop, and Deploy Effective Software Systems Using the Advanced Constructs of Rust. by Sharma, Rahul

Table of Contents: “…Chapter 1: Getting Started with Rust -- Chapter 2: Managing Projects with Cargo -- Chapter 3: Tests, Documentation, and Benchmarks -- Chapter 4: Types, Generics, and Traits -- Chapter 5: Memory Management and Safety -- Chapter 6: Error Handling -- Chapter 7: Advanced Concepts -- Chapter 8: Concurrency -- Chapter 9: Metaprogramming with Macros -- Chapter 10: Unsafe Rust and Foreign Function Interfaces -- Chapter 11: Logging -- Chapter 12: Network Programming in Rust -- Chapter 13: Building Web Applications with Rust -- Chapter 14: Lists, Lists, and More Lists -- Chapter 15: Robust Trees -- Chapter 16: Exploring Maps and Sets -- Chapter 17: Collections in Rust -- Chapter 18: Algorithm Evaluation -- Chapter 19: Ordering Things -- Chapter 20: Finding Stuff -- Chapter 21: Random and Combinatorial -- Chapter 22: Algorithms of the Standard Library.…”
Full text (MFA users only)

Python unlocked : become more fluent in Python--learn strategies and techniques for smart and high-performance Python programming by Tigeraniya, Arun

Table of Contents: “…Method resolution orderSuper's superpowers; Using language protocols in classes; Iteration protocol; Context manager protocol; Using abstract classes; Summary; Chapter 3: Functions and Utilities; Defining functions; Decorating callables; Utilities; Summary; Chapter 4: Data Structures and Algorithms; Python built-in data structures; Python library data structures; Third party data structures; Arrays/List; Binary tree; Sorted containers; Trie; Algorithms on scale; Summary; Chapter 5: Elegance with Design Patterns; Observer pattern; Strategy pattern; Singleton pattern; Template pattern.…”
Full text (MFA users only)

Geometric Function Theory In Several Complex Variables, Proceedings Of A Satellite Conference To The Int'l Congress Of Mathematicians In Beijing 2002. by FitzGerald, Carl H.

Table of Contents: “…Greiner and Jingzhi Tie); Defective values of double Meissel's formula and reduction of space-time requirement of Meissel-Lehmer-Lagarias-Odlyzko's algorithm an experimental program to find T(1021) (by Chen Guangxiao); Hardy space of holomorphic functions in infinite complex variables (by Zeqian Chen); The law of the iterated logarithm for pluriharmonic functions in the unit ball of Cn (by Zeqian Chen, Caiheng Ouyang).…”
Full text (MFA users only)

Electronic design automation : synthesis, verification, and test

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)

Deterministic global optimization : an introduction to the diagonal approach by Sergeyev, Yaroslav D., 1963-, Kvasov, Dmitri E.

Table of Contents: “…3.1 General Diagonal Scheme3.2 Analysis of Traditional Diagonal Partition Schemes; 3.3 Non-redundant Diagonal Partition Strategy; 4 Global Optimization Algorithms Based on the Non-redundant Partitions ; 4.1 Multiple Estimates of the Lipschitz Constant; 4.2 Derivative-Free Diagonal Method MultL; 4.2.1 Theoretical Background of MultL: Lower Bounds; 4.2.2 Theoretical Background of MultL: Finding Non-dominated Hyperintervals; 4.2.3 Description of the MultL Algorithm and its Convergence Analysis; 4.3 One-Point-Based Method MultK for Differentiable Problems.…”
Full text (MFA users only)

Machine learning with R quick start guide : a beginner's guide to implementing machine learning techniques from scratch using R 3.5 by Pastor Sanz, Iván

Table of Contents: “…Accessing components and elements in a listData frames; Accessing elements in data frames; Functions of data frames; Importing or exporting data; Working with functions; Controlling code flow; All about R packages; Installing packages; Necessary packages; Taking further steps; Background on the financial crisis; Summary; Chapter 2: Predicting Failures of Banks -- Data Collection; Collecting financial data; Why FDIC?; Listing files; Finding files; Combining results; Removing tables; Knowing your observations; Handling duplications; Operating our problem; Collecting the target variable…”
Full text (MFA users only)

Computer Mathematics : Proceedings of the Fifth Asian Symposium (Ascm 2001). by Shirayanagi, Kiyoshi

Table of Contents: “…Preface ; Invited Talks ; Finding All the Solutions of Cyclic 9 Using Grobner Basis Techniques ; On the Complexity of Computing Determinants (Extended Abstract) ; Papers.…”
Full text (MFA users only)

Pattern discovery in biomolecular data : tools, techniques, and applications

Table of Contents: “…Discovering patterns in DNA sequences by the algorithmic significance method / Aleksandar Milosavljevic -- Assembling blocks / Jorja G. …”
Full text (MFA users only)

Focus on artificial neural networks

Table of Contents: “…ARTIFICIAL NEURAL NETWORKS (ANNS) -- 3. MICROEMULSIONS -- 4. APPLICATION OF ANNS IN THE DEVELOPMENT OF MICROEMULSION DRUG DELIVERY SYSTEMS -- 4.1. …”
Full text (MFA users only)

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

Table of Contents: “…2.4 Techniques for Proving Inapproximability Results for String Barcoding Problems2.5 Heuristic Algorithms for String Barcoding Problems; 2.6 Conclusion; Acknowledgments; References; Chapter 3: Alignment-Free Measures for Whole-Genome Comparison; 3.1 Introduction; 3.2 Whole-Genome Sequence Analysis; 3.3 Underlying Approach; 3.4 Experimental Results; 3.5 Conclusion; Author's Contributions; 3.6 Acknowledgments; References; Chapter 4: A Maximum Likelihood Framework for Multiple Sequence Local Alignment; 4.1 Introduction; 4.2 Multiple Sequence Local Alignment; 4.3 Motif Finding Algorithms.…”
Full text (MFA users only)

Machine Learning with Core ML : an IOS Developer's Guide to Implementing Machine Learning in Mobile Apps. by Newnham, Joshua

Table of Contents: “…Learning algorithms Auto insurance in Sweden; Supported learning algorithms; Considerations ; Summary; Chapter 3: Recognizing Objects in the World; Understanding images; Recognizing objects in the world; Capturing data ; Preprocessing the data; Performing inference ; Summary ; Chapter 4: Emotion Detection with CNNs; Facial expressions; Input data and preprocessing ; Bringing it all together; Summary ; Chapter 5: Locating Objects in the World; Object localization and object detection ; Converting Keras Tiny YOLO to Core ML; Making it easier to find photos; Optimizing with batches; Summary.…”
Full text (MFA users only)

Metaheuristics for vehicle routing problems. by Labadie, Nacima

Table of Contents: “…Memetic algorithm; 4.1.3. Memetic algorithm with population management; 4.1.4. …”
Full text (MFA users only)

Industrial control systems

Table of Contents: “…EXTRACTIVE FERMENTATION PROCESS FOR BIOETHANOL PRODUCTION ; 3. PLANT MODEL BASED ON ANN ; 3.1. ANN Configurations.…”
Full text (MFA users only)

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.…”
Full text (MFA users only)

Euro-dollar real exchange rate dynamics in an estimated two-country model : what is important and what is not by Rabanal, Pau, Tuesta, Vicente

Full text (MFA users only)

Placement preparation : more than 1000 questions by Parthasarathy, S.

Full text (MFA users only)

Comprehensive Ruby Programming. by Hudgens, Jordan

Table of Contents: “…Implementing a prime number counting algorithm -- How to code the power digit sum algorithm -- Implementing a humanize counting algorithm -- Implementing a date algorithm -- How to code a Fibonacci digit counter -- Implementing a permutation algorithm -- Implementing an amicable number algorithm -- Implementing a factorial algorithm -- Implementing an even Fibonacci number algorithm -- Implementing the least common multiple -- Summary -- Chapter 19: Machine Learning -- Big data analysis -- Basic decision tree implementation -- Addition of attributes -- Addition of training data and its values -- Calling the ID3 method -- Function of the train method -- Addition of the test method -- Setting up decision variables -- Print the results out -- Testing the program -- Advantage of decision trees over if ... else statements -- How to develop a big data analysis application in Ruby -- Summary -- Index.…”
Full text (MFA users only)

MATLAB for Machine Learning. by Ciaburro, Giuseppe

Table of Contents: “…Multiple linear regression with categorical predictorPolynomial regression; Regression Learner App; Summary; Chapter 5: Pattern Recognition through Classification Algorithms; Predicting a response by decision trees; Probabilistic classification algorithms -- Naive Bayes; Basic concepts of probability; Classifying with Naive Bayes; Bayesian methodologies in MATLAB; Describing differences by discriminant analysis; Find similarities using nearest neighbor classifiers; Classification Learner app; Summary; Chapter 6: Identifying Groups of Data Using Clustering Methods; Introduction to clustering.…”
Full text (MFA users only)

Applications of swarm intelligence

Table of Contents: “…Algorithm for Ms3 ""; ""4.4. Ms4: Combination of Ms1 and Ms2 ""; ""4.5. …”
Full text (MFA users only)