Search Results - (((((((want OR alter) OR wind) OR semantic) OR cantor) OR anne) OR halted) OR wwanting) algorithms.

The attacker's advantage : turning uncertainty into breakthrough opportunities by Charan, Ram

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Advances in mechatronics, robotics and automation II : selected, peer reviewed papers from the 2014 2nd International Conference on Mechatronics, Robotics and Automation (ICMRA 201...

Table of Contents: “…Advances in Mechatronics, Robotics and Automation II; Preface and Conference Organization; Table of Contents; Chapter 1: Signal Processing System Design and Implementation; A Method of Multi-Antenna Signal Time-Delay Alignment Algorithm for Cyclostationary Signals; Analysis of Ground-Based Navigation Signal Coverage on Performance-Based Navigation; Detection and Analysis of Rats' Bioelectromagnetic Signal; Fault Diagnosis of Gearbox in Wind Turbine Based on Wavelet Transform and Support Vector Machine; Research of Multi-Channel Audio Data Acquisition System Based on FPGA and ARM.…”
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Stairs 2006 : Proceedings of the Third Starting AI Researchers' Symposium

Table of Contents: “…A Comparison of Two Machine-Learning Techniques to Focus the Diagnosis TaskArgumentation Semantics for Temporal Defeasible Logic; NEWPAR: An Optimized Feature Selection and Weighting Schema for Category Ranking; Challenges and Solutions for Hierarchical Task Network Planning in E-Learning; Invited Talks; Artificial Intelligence and Unmanned Aerial Vehicles; Writing a Good Grant Proposal; Author Index…”
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Mixed Models : Theory and Applications with R. by Demidenko, Eugene

Table of Contents: “…2.9 Derivatives of the log-likelihood function -- 2.10 Newton-Raphson algorithm -- 2.11 Fisher scoring algorithm -- 2.11.1 Simplified FS algorithm -- 2.11.2 Empirical FS algorithm -- 2.11.3 Variance-profile FS algorithm -- 2.12 EM algorithm -- 2.12.1 Fixed-point algorithm -- 2.13 Starting point -- 2.13.1 FS starting point -- 2.13.2 FP starting point -- 2.14 Algorithms for restricted MLE -- 2.14.1 Fisher scoring algorithm -- 2.14.2 EM algorithm -- 2.15 Optimization on nonnegative definite matrices -- 2.15.1 How often can one hit the boundary? …”
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Future Farming. by Shukla, Praveen Kumar

Table of Contents: “…PROPOSED METHODOLOGY -- Pre-processing -- Leaf Image from Plants -- Segmentation Model Using Improved Canny Algorithm -- Steps of Improved Canny Algorithm -- Leaf Image Feature Selection Using Hybrid Black Widow Optimization Algorithm with Mayfly Optimization Algorithm (BWO-MA) -- Pseudo-Code of the Hybrid (BWO-MA) Algorithm -- Output: Objective Function's -RMSE -- Leaf Image Classification Using (BWO-MA) with ANN -- Hyper-Parameter Tuning With (BWO-MA) -- RESULT AND DISCUSSION -- Dataset Description -- Evaluation & Results -- CONCLUSION -- REFERENCES…”
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Rough fuzzy image analysis : foundations and methodologies

Table of Contents: “…1. Cantor, fuzzy, near, and rough sets in image analysis / James F. …”
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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…”
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Handbook of Modal Logic. by Blackburn, Patrick

Table of Contents: “…13 Quantified Modal Logic13.1 Syntax and Semantics; 13.2 Constant Domain Tableaus; 13.3 Soundness and Completeness; 13.4 Variations; 14 Conclusion; Bibliography; Chapter 3 Complexity of Modal Logic; 1 Introduction; 1.1 Examples of decision problems in modal logic; 1.2 A simple and a hard problem; 1.3 The model checking problem; 1.4 The consequence problem; 1.5 A tiling logic; 2 Decision algorithms; 2.1 Selection of points; 2.2 Filtration; 2.3 Hintikka set elimination; 2.4 Hintikka set elimination without constraints; 2.5 Forcing exponentially deep paths; 2.6 Tree automata; 2.7 Pseudo-models.…”
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Enterprise artificial intelligence transformation : a playbook for the next generation of business and technology leaders by Haq, Rashed

Table of Contents: “…Types of Uses for Machine Learning -- Types of Machine Learning Algorithms -- Supervised, Unsupervised, and Semisupervised Learning -- Making Data More Useful -- Semantic Reasoning -- Applications of AI -- PART II Artificial Intelligence in the Enterprise -- Chapter 3 AI in E-Commerce and Retail -- Digital Advertising -- Marketing and Customer Acquisition -- Cross-Selling, Up-Selling, and Loyalty -- Business-to-Business Customer Intelligence -- Dynamic Pricing and Supply Chain Optimization -- Digital Assistants and Customer Engagement -- Chapter 4 AI in Financial Services -- Anti-Money Laundering.…”
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OpenCV with Python by example : build real-world computer vision applications and develop cool demos using OpenCV for Python by Joshi, Prateek

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Fast sequential Monte Carlo methods for counting and optimization by Rubinstein, Reuven Y.

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Advanced Control and Optimization Paradigms for Energy System Operation and Management. by Pal, Kirti

Table of Contents: “…3.4: Procedure -- 3.4.1: Solar Photovoltaic System -- 3.4.2: Wind Turbine -- 3.4.3: Battery Energy Storage System -- 3.4.4: Diesel Generator -- 3.5: Modelling of the HRES with Different kinds of Batteries -- 3.6: System Metrics -- 3.6.1: Economic Metrics -- 3.6.2: Technical Performance of the Overall System -- 3.6.3: Contribution of Solar PV -- 3.6.4: Contribution of Wind Turbine and Diesel Generator -- 3.6.5: Technical Specification of Different Batteries Used in HRES -- 3.7: State of Charge of Battery -- 3.8: Emissions through a Different System with Different Batteries -- 3.9: Conclusions…”
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Language and logos : studies in theoretical and computational linguistics

Table of Contents: “…CONTENTS -- Preface -- Part I Syntax -- A Spurious Genitive Puzzle in Polish -- Semantic Type Effects on Crossing Movement in German -- Me and Chomsky -- On the Typology of Verb Second -- Movement from Verb-Second Clauses Revisited -- Spurious Ambiguities and the Parentheticals Debate -- Part II Semantics -- On Squeamishness of the Royal Kind -- Information Structure of schon -- When- Clauses, Factive Verbs and Correlates -- The Proof Theory of Partial Variables -- Brentano's Apple -- How to Interpret Expletive Negation under bevor in German…”
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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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Rediscovering mathematics : you do the math by Simonson, Shai

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Advanced Methods and Technologies for Agent and Multi-Agent Systems. by Edited by

Table of Contents: “…""Role and Member Selection in Team Formation Using Resource Estimation""""Incorporating Explicit Coordination Mechanisms by Agents to Obtain Green Waves""; ""Communication Leading to Coalition Nash Equilibrium I""; ""Agent-Based Optimization""; ""An Agent-Based Cooperative Population Learning Algorithm for Vehicle Routing Problem with Time Windows""; ""Mobile Agent-based Dynamic Resource Allocation Method for Query Optimization in Data Grid Systems""; ""Memetic Multi-Agent Computing in Difficult Continuous Optimisation""; ""Web Services and Semantic Web""…”
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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…”
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Artificial intelligence with Python : build real-world artificial intelligence applications with Python to intelligently interact with the world around you by Joshi, Prateek

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Hierarchical Protection for Smart Grids. by Ma, Jing

Table of Contents: “…3.3 Local Area Protection for Centralized Renewable Energy3.3.1 Connection Form of a Wind Farm and its Protection Configuration; 3.3.2 Adaptive Distance Protection Scheme for Wind Farm Collector Lines; 3.3.3 Differential Protection Scheme for Wind Farm Outgoing Transmission Line; 3.4 Local Area Protection for Distributed Renewable Energy; 3.4.1 Adaptive Protection Approach for a Distribution Network Containing Distributed Generation; 3.4.2 Islanding Detection Method; 3.5 Summary; References; Chapter 4 Topology Analysis; 4.1 Introduction; 4.2 Topology Analysis for the Inner Substation.…”
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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. …”
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