Search Results - (((((((kant OR want) OR semantic) OR arts) OR cantor) OR anne) OR maarten) OR mantis) algorithms.

New autonomous systems by Cardon, Alain, 1946-, Itmi, Mhamed

Table of Contents: “…Intro -- Table of Contents -- Title -- Copyright -- Introduction -- List of Algorithms -- 1 Systems and their Design -- 1.1. Modeling systems -- 1.2. …”
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Numerical linear algebra with applications : using MATLAB by Ford, William H.

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Data Analytics in Bioinformatics : A Machine Learning Perspective. by Satpathy, Rabinarayan

Table of Contents: “…3.4.1 Comparative Analysis of ANN With Broadly Used Traditional ML Algorithms -- 3.5 Critical Analysis -- 3.6 Conclusion -- References -- Part 2: MACHINE LEARNING AND GENOMIC TECHNOLOGY, FEATURE SELECTION AND DIMENSIONALITY REDUCTION -- 4 Dimensionality Reduction Techniques: Principles, Benefits, and Limitations -- 4.1 Introduction -- 4.2 The Benefits and Limitations of Dimension Reduction Methods -- 4.3 Components of Dimension Reduction -- 4.3.1 Feature Selection -- 4.3.2 Feature Reduction -- 4.4 Methods of Dimensionality Reduction -- 4.4.1 Principal Component Analysis (PCA)…”
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Cybernetic Intelligence

Table of Contents: “…Editorial advisory board; Preface; Editorial; Second-order cybernetics and enactive perception; Semantic category theory cognition and conceptual reference; Bipolar logic and probabilistic interpretation; Cooperative clans; Future reasoning machines: mind and body; Machine vision methods for autonomous micro-robotic systems; Optimisation enhancement using self-organising fuzzy control; Intelligent agents and distributed models for cooperative task support; Landscape classification and problem specific reasoning for genetic algorithms; Business cybernetics: a provocative suggestion.…”
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Modeling and optimization of air traffic by Delahaye, Daniel

Table of Contents: “…pt. 1: Optimization and artificial evolution -- Optimization: State of the art -- Genetic algorithms and improvements -- A new concept for genetic algorithms based on order statistics -- pt. 2: Applications to air traffic control -- Air traffic control -- Contributions to airspace sectorization -- Contribution to traffic assignment -- Airspace congestion metrics -- Conclusion and future perspectives.…”
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Metaheuristic applications in structures and infrastructures

Table of Contents: “…Metaheuristic Algorithms in Modeling and Optimization -- A Review on Traditional and Modern Structural Optimization: Problems and Techniques -- Particle Swarm Optimization in Civil Infrastructure Systems: State-of-the-Art Review -- Evolution Strategies-Based Metaheuristics in Structural Design Optimization -- Multidisciplinary Design and Optimization Methods -- Cost Optimization of Column Layout Design of Reinforced Concrete Buildings -- Layout Design of Beam-Slab Floors by a Genetic Algorithm -- Optimum Design of Skeletal Structures via Big Bang-Big Crunch Algorithm -- Truss Weight Minimization Using Hybrid Harmony Search and Big Bang-Big Crunch Algorithms -- Graph Theory in Evolutionary Truss Design Optimization -- Element Exchange Method for Stochastic Topology Optimization -- Evolutionary Path-Dependent Damper Optimization for Variable Building Stiffness Distributions -- Application of Genetic Algorithms in Ground Motion Selection for Seismic Analysis -- Optimization of Tuned Mass Damper with Harmony Search -- Identification of Passive Devices for Vibration Control by Evolutionary Algorithms -- Structural Optimization for Frequency Constraints -- Optimum Performance-Based Seismic Design of Frames Using Metaheuristic Optimization Algorithms -- Expression Programming Techniques for Formulation of Structural Engineering Systems -- An Evolutionary Divide-and-Conquer Strategy for Structural Identification -- Swarm Intelligence for Large-Scale Optimization in Construction Management -- Network-Level Infrastructure Management Based on Metaheuristics -- Large-Scale Maintenance Optimization Problems for Civil Infrastructure Systems -- Metaheuristic Applications in Bridge Infrastructure Maintenance Scheduling Considering Stochastic Aspects of Deterioration.…”
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Language engineering for lesser-studied languages

Table of Contents: “…Derzhanski -- Computational morphology for lesser-studied languages / Kemal Olfazer -- Practical syntastic processing of flexible word order languages with dynamic syntax / David Tugwell -- Computation field semantics : acquiring an ontological-semantic lexicon for a new language / Sergei Nirenburg and Marjorie McShane -- Applying machine translation for low- and middle-density languages / Stella Markantonatou [and others] -- Language resources for semitic languages : challenges and solutions / Shuly Wintner -- Low-density language strategies for Persian and Armenian / Karine Megerdoomian.…”
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Theory of information : fundamentality, diversity and unification by Burgin, M. S. (Mark Semenovich)

Table of Contents: “…Algorithmic information theory based on recursive algorithms : recursive approach. 5.3. …”
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Media technologies : essays on communication, materiality, and society

Table of Contents: “…Bowker -- "What Do We Want?" "Materiality!" "When Do We Want It?" "Now!" …”
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Agent-based computing

Table of Contents: “…Analysis of Algorithm -- 2.1.1. Chain-Like Agent Structure -- 2.1.2. …”
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A companion to rhetoric and rhetorical criticism

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Sharing economy and big data analytics by Sedkaoui, Soraya, Khelfaoui, Mounia

Table of Contents: “…Not Without Big Data Algorithms. Linear Regression -- Classification Algorithms -- Cluster Analysis -- Conclusion -- References -- Index -- Other titles from iSTE in Information Systems, Web and Pervasive Computing.…”
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Introduction to imprecise probabilities

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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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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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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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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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