Search alternatives:
learning algorithm » learning algorithms (Expand Search)
method algorithm » mould algorithm (Expand Search)
a learning » _ learning (Expand Search)
learning algorithm » learning algorithms (Expand Search)
method algorithm » mould algorithm (Expand Search)
a learning » _ learning (Expand Search)
-
61
Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
Get full text
-
62
Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…This is in contrast to previous approaches where GA is applied to the whole sequence. The proposed method is compared with previous GA-based approaches. …”
Get full text
article -
63
A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text
Published 2019“…The previously published research on Arabic ontology learning from text falls into three categories: developing manually hand-crafted rules, using ordinary supervised/unsupervised machine learning algorithms, or a hybrid of these two approaches. …”
Get full text
Get full text
-
64
Assessment of static pile design methods and non-linear analysis of pile driving
Published 2006“…The pile/soil interaction system is described by a mass/spring/dashpot system where the properties of each component are derived from rigorous analytical solutions or finite element analysis. The outcome of this research is an algorithm that can be used to predict pile displacement and driving stresses. …”
Get full text
Get full text
Get full text
masterThesis -
65
Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…</p><h3>Objective</h3><p dir="ltr">In this paper, we propose a machine learning–based approach for identifying research gaps through the analysis of scientific literature. …”
-
66
Efficient methods and techniques for the open-shop scheduling problem. (c2006)
Published 2006Get full text
Get full text
masterThesis -
67
Learning control algorithms for tracking "slowly" varying trajectories
Published 1997“…This is due to the requirement that all learning algorithms assume that a desired output is given a priori over the time duration t /spl isin/ ~0,T\. …”
Get full text
Get full text
Get full text
Get full text
article -
68
Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise
Published 2005“…The state function does not need to satisfy a Lipschitz condition. This work also provides a recursive algorithm that generates the appropriate learning gain functions that meet the arbitrary high precision output tracking objective. …”
Get full text
Get full text
Get full text
Get full text
article -
69
Robustness and convergence rate of a discrete‐time learning control algorithm for a class of nonlinear systems
Published 1999“…In this paper, we apply a discrete‐time learning algorithm to a class of discrete‐time varying nonlinear systems with affine input action and linear output having relative degree one. …”
Get full text
Get full text
Get full text
Get full text
article -
70
Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method
Published 2021“…This paper addresses the high volatility of PV power by proposing a precise and reliable ensemble learning model for short-term PV power generation forecasting. …”
-
71
A hybrid distributed test generation method using deterministic and genetic algorithms
Published 2017“…In this work, we present a distributed method for combinational test generation. The method is based on a hybrid approach that combines both deterministic and genetic approaches. …”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
72
Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review
Published 2023“…Deepening grid integration of photovoltaic and wind systems is introducing unforeseen uncertainties for the electricity sector. As a cutting-edge machine learning technology, deep reinforcement learning (DRL) breakthroughs have been in the spotlight over the last few years with potential contributions to PS stability (PSS). …”
-
73
-
74
-
75
Metaheuristic Algorithm for State-Based Software Testing
Published 2018“…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …”
Get full text
Get full text
Get full text
Get full text
article -
76
Optimal selection of the forgetting matrix into an iterative learning control algorithm
Published 2005“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
Get full text
Get full text
Get full text
Get full text
article -
77
Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
Published 2022“…A Master of Science thesis in Computer Engineering by Ali Reza Sajun entitled, “Exploring Semi-Supervised Learning Algorithms for Camera Trap Images”, submitted in August 2022. …”
Get full text
doctoralThesis -
78
Application of Red Deer Algorithm in Optimizing Complex functions
Published 2021“…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
Get full text
Get full text
-
79
Rigorous Phase Equilibrium Calculation Methods for Strong Electrolyte Solutions: The Isothermal Flash
Published 2022“…It is shown that the Lagrange multiplier which corresponds to the electro-neutrality constraint has theoretical meaning and direct relation to the electrostatic potential difference between inhomogeneous phases. Based on the new approach, named Electrochemical Ionic Approach (EIA), two new numerical methods are presented; a successive substitution method similar to the classical Rachford-Rice method and a second-order one, which is based on Newton's method. …”
-
80
Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem
Published 2018“…The GA method is implemented in java, and the improvement of the initial solution is exhibited by the results of the experiments based on the specified constraints and requirements.…”
Get full text
Get full text
Get full text
Get full text
article