Ant lion optimizer: theory, literature review, and application in multi-layer perceptron neural networks
This chapter proposes an efficient hybrid training technique (ALOMLP) based on the Ant
Lion Optimizer (ALO) to be utilized in dealing with Multi-Layer Perceptrons (MLPs) neural …
Lion Optimizer (ALO) to be utilized in dealing with Multi-Layer Perceptrons (MLPs) neural …
Optimizing connection weights in neural networks using the whale optimization algorithm
The learning process of artificial neural networks is considered as one of the most difficult
challenges in machine learning and has attracted many researchers recently. The main …
challenges in machine learning and has attracted many researchers recently. The main …
An efficient hybrid multilayer perceptron neural network with grasshopper optimization
This paper proposes a new hybrid stochastic training algorithm using the recently proposed
grasshopper optimization algorithm (GOA) for multilayer perceptrons (MLPs) neural …
grasshopper optimization algorithm (GOA) for multilayer perceptrons (MLPs) neural …
How effective is the Grey Wolf optimizer in training multi-layer perceptrons
S Mirjalili - Applied intelligence, 2015 - Springer
This paper employs the recently proposed Grey Wolf Optimizer (GWO) for training Multi-
Layer Perceptron (MLP) for the first time. Eight standard datasets including five classification …
Layer Perceptron (MLP) for the first time. Eight standard datasets including five classification …
Develo** reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information
Reservoirs are fundamental human‐built infrastructures that collect, store, and deliver fresh
surface water in a timely manner for many purposes. Efficient reservoir operation requires …
surface water in a timely manner for many purposes. Efficient reservoir operation requires …
A de-ann inspired skin cancer detection approach using fuzzy c-means clustering
As per recent developments in medical science, the skin cancer is considered as one of the
common type disease in human body. Although the presence of melanoma is viewed as a …
common type disease in human body. Although the presence of melanoma is viewed as a …
Training feedforward neural networks using multi-verse optimizer for binary classification problems
This paper employs the recently proposed nature-inspired algorithm called Multi-Verse
Optimizer (MVO) for training the Multi-layer Perceptron (MLP) neural network. The new …
Optimizer (MVO) for training the Multi-layer Perceptron (MLP) neural network. The new …
Wind power forecast using wavelet neural network trained by improved Clonal selection algorithm
With the integration of wind farms into electric power grids, an accurate wind power
prediction is becoming increasingly important for the operation of these power plants. In this …
prediction is becoming increasingly important for the operation of these power plants. In this …
Short-term load forecast of microgrids by a new bilevel prediction strategy
Microgrids are a rapidly growing sector of smart grids, which will be an essential component
in the trend toward distributed electricity generation. In the operation of a microgrid …
in the trend toward distributed electricity generation. In the operation of a microgrid …
A neural network-based framework for financial model calibration
A data-driven approach called CaNN (Calibration Neural Network) is proposed to calibrate
financial asset price models using an Artificial Neural Network (ANN). Determining optimal …
financial asset price models using an Artificial Neural Network (ANN). Determining optimal …