Springer Estimating Ore Grade Using Evolutionary Machine Learning Models

Estimating Ore Grade Using Evolutionary Machine Learning Models

Springer

Advanced Machine Learning with Evolutionary and Metaheuristic Techniques (Computational Intelligence Methods and Applications)

Application of Machine Learning in Slope Stability Assessment

Evolutionary Data Clustering: Algorithms and Applications (Algorithms for Intelligent Systems)

Machine Learning in Educational Sciences: Approaches, Applications and Advances

Machine Learning and Optimization for Engineering Design (Engineering Optimization: Methods and Applications)

Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization (Genetic and Evolutionary Computation)

Springer

Computational and Machine Learning Tools for Archaeological Site Modeling (Springer Theses)

Generalized Matrix Inversion: A Machine Learning Approach

Machine Learning for Materials Discovery: Numerical Recipes and Practical Applications (Machine Intelligence for Materials Science)

Computational and Machine Learning Tools for Archaeological Site Modeling (Springer Theses)

Springer

Feature and Dimensionality Reduction for Clustering with Deep Learning (Unsupervised and Semi-Supervised Learning)

Mathematical Optimization and Evolutionary Algorithms with Applications

Dirty Data Processing for Machine Learning

Deep Learning in Wireless Communications

Springer

Coseismic Landslides: Intelligent Prediction and Recognition

Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python

Handbook of Trustworthy Federated Learning (Springer Optimization and Its Applications)

Machine Learning Applied to Composite Materials (Composites Science and Technology)

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Use Cases and Emerging Challenges

Communication Efficient Federated Learning for Wireless Networks

Springer

Deep Learning and Practice with MindSpore (Cognitive Intelligence and Robotics)

Springer

Harmonic Estimation and Forecasting in Sparsely Monitored Uncertain Power Systems: Probabilistic and Machine Learning Approaches (Springer Theses)

Springer Automating Data-Driven Modelling of Dynamical Systems

Springer