Search Results - (( developing learning evolution algorithm ) OR ( java application need algorithm ))
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1
Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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2
Differential evolution for neural networks learning enhancement
Published 2008“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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3
Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia
Published 2024“…The final optimum learning algorithm was selected based on the performance values (regression…”
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Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development
Published 2025Subjects: “…Algorithms development…”
Review -
5
Direct approach for mining association rules from structured XML data
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6
An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…It also has the ability to learn, recognize, and remember, thus providing the solid foundation for the development of Artificial Immune System (AIS). …”
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7
Real-Time Video Processing Using Native Programming on Android Platform
Published 2012“…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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Machine learning and deep learning approaches for cybersecurity: a review
Published 2022“…It discusses recent machine learning and deep learning work with various network implementations, applications, algorithms, learning approaches, and datasets to develop an operational intrusion detection system.…”
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9
Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. In essence, a neural network is an attempt to mimic the extremely complex human brain system, which is building an artificial brain that is able to self-learn intelligently. …”
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10
Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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11
Automating commercial video game development using computational intelligence
Published 2011“…Pac-man. The resulting algorithm is referred to as an Evolution Strategies Neural Network or ESNet. …”
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Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots
Published 2006“…A simulated Khepera robot is evolved by a Pareto-frontier Differential Evolution (POE) algorithm, and learned through a 3-layer feed-forward artificial neural network, attempting to simultaneously fulfill two conflicting objectives of maximizing robot phototaxis behavior while minimizing the neural network's hidden neurons by generating a Pareto optimal set of controllers. …”
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13
A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter
Published 2018“…Based on observations made from stochastic dynamical systems, we consider the issue of parameter learning, and a related state estimation problem. We develop a Markov Chain Monte Carlo (MCMC) algorithm, which is an iterative method, for parameter inference. …”
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14
Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…This reason motivated the researchers to exploit the evolution of machine learning to develop water level forecasting systems that were characterized by accuracy, simplicity and low cost. …”
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15
Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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16
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Network game (Literati) / Chung Mei Kuen
Published 2003“…Therefore, efficient and robust servers that process separate client connections in separate threads are needed. Java applet is a well-known and widely used example of mobile code (a variation on the traditional client-server model). …”
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18
A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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A review on monocular tracking and mapping: from model-based to data-driven methods
Published 2022“…Finally, the popular benchmarks available for developing and evaluating these algorithms are presented along with a comparative study on a different class of algorithms. …”
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Automated time series forecasting
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