A Hybrid Deep Learning Model with Evolutionary Algorithm for Short ...

There are many techniques to amicably forecast the demand of electricity. Amongst which the hybrid models show the best result. In this study, a hybrid method ...

The experimental results show that the proposed hybrid model of GA-LSTM network surpasses the other standard models such as support vector machine (SVM), ...

Hybrid models based on genetic algorithm and deep learning ...

In this study, we propose two hybrid models using genetic algorithm (GA) and deep learning algorithms of Stacked Autoencoder (SAE) and Convolutional Neural ...

Hybrid deep learning and evolutionary algorithms for accurate cloud ...

This study proposes a hybrid model combining both state-of-the-art deep learning models and evolutionary algorithms for workload prediction.

Harnessing the power of hybrid deep learning algorithm for the ...

This study proposes a forecasting framework using an integrated model of the convolutional neural network (CNN), long short-term memory (LSTM), and gated ...

A novel hybrid deep learning model with ARIMA Conv-LSTM ...

A reliable estimation algorithm can dynamically predict urban traffic flow with acceptable accuracy in the short and long term based on historical traffic data.

A hybrid model integrating long short-term memory with adaptive ...

Common machine learning methods include deep learning networks (DLNs), BP neural networks, genetic algorithms (GA), support vector machines (SVM) ...

Short-Term Streamflow Forecasting Using Hybrid Deep Learning ...

... Hybrid Deep Learning Model Based on Grey Wolf Algorithm for Hydrological Time Series ... Efficiency of Regression, ANN and ANN-algorithm Genetic Hybrid Models in ...

Hybrid Evolutionary Algorithms: Methodologies, Architectures, and ...

... Machine Learning Approach to Modeling, Ginn & Co., Needham, MA. Google ... Wang L (2005) A hybrid genetic algorithm-neural network strategy for ...

Enhancing Viral DNA Sequence Classification Using Hybrid Deep ...

... Short-Term Memory (LSTM) model architectures. Three ... Hybrid Deep Learning Models and Genetic Algorithm Optimization (January 11, 2024).

Awesome Evolutionary Deep Learning Algorithms

... Evolutionary Neural Architecture Search [2020, Zhang et al.] [arXiv]; An Evolutionary Deep Learning Method for Short-term Wind Speed Prediction: A Case Study ...

Optimizing hybrid deep learning models for drug‐target interaction ...

Through thorough comparative analysis, we evaluate the performance of these evolutionary algorithms in enhancing the CSAN‐BiLSTM‐Att model's ...

A Hybrid Competitive Evolutionary Neural Network Optimization ...

Section 3 presents the most significant results from related state-of-the-art models, in terms of using evolutionary algorithms for general-purpose problems, ...

A hybrid evolutionary algorithm approach for estimating the

To train the GP algorithm we use MARKOV, an accurate algorithm for calculating numerically the exact throughput of short exponential production lines. A few ...

Evolutionary Machine Learning: A Survey - ACM Digital Library

EC algorithms have recently been used to improve the performance of Machine Learning (ML) models and the quality of their results. Evolutionary approaches can ...

Evolving machine learning and deep learning models using ...

... evolutionary algorithms and the conventional ML and DL methods. Specifically, two Firefly Algorithm based evolutionary clustering models are ...

[PDF] A Novel Evolutionary-Based Deep Convolutional Neural ...

An advanced short-term wind power forecasting framework based on the optimized deep neural network models ... The proposed hybrid evolutionary algorithm ...

Enhancing Arabic Phishing Email Detection: A Hybrid Machine ...

The algorithm evaluates these chromosomes based on a fitness function, which typically measures the performance of a machine learning model using the selected ...

Dung beetle optimization algorithm-based hybrid deep learning ...

A hybrid model combining self-attention temporal convolutional networks (SATCN) with bidirectional long short-term memory networks (BiLSTM) was developed

Survey on Evolutionary Deep Learning: Principles, Algorithms ...

According to the DL pipeline, we systematically introduce EDL methods ranging from data preparation, model generation, to model deployment with a new taxonomy ( ...