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 …

IoT-based systems are complex and dynamic aggregations of entities (Smart Objects) which
usually lack decentralized control. Swarm Intelligence systems are decentralized, self …

This paper proposes a new hybrid stochastic training algorithm using the recently proposed
grasshopper optimization algorithm (GOA) for multilayer perceptrons (MLPs) neural …

Faulty structural design may cause multistory reinforced concrete (RC) buildings to collapse
suddenly. All attempts are directed to avoid structural failure as it leads to human life danger …

Today, stock market has important function and it can be a place as a measure of economic
position. People can earn a lot of money and return by investing their money in the stock …

Artificial neural network (ANN) is an information processing paradigm that loosely models
the thinking patterns of the human brain with specifications such as real-time learning, self …

Vibration-based damage detection methods have become widely used because of their
advantages over traditional methods. This paper presents a new approach to identify the …

The search for powerful optimizers has led to the development of a multitude of
metaheuristic algorithms inspired from all areas. This work focuses on the animal kingdom …

In the present study, a new algorithm is developed for neural network training by combining
a gradient-based and a meta-heuristic algorithm. The new algorithm benefits from …

The optimal generation of initial connection weight parameters and dynamic updating
strategies of connection weights are critical for adjusting the performance of back …