A constraint-based genetic algorithm for optimizing neural network architectures for detection of loss of coolant accidents of nuclear power plants

© 2018 Elsevier B.V. The loss of coolant accident (LOCA) of a nuclear power plant (NPP) is a severe accident in the nuclear energy industry. Nowadays, neural networks have been trained on nuclear simulation transient datasets to detect LOCA. This paper proposes a constraint-based genetic algorithm (GA) to find optimised 2-hidden layer network architectures for detecting LOCA of a NPP. The GA uses a proposed constraint satisfaction algorithm called random walk heuristic to create an initial population of neural network architectures of high performance. At each generation, the GA population is split into a sub-population of feature subsets and a sub-population of 2-hidden layer architectures to breed offspring from each sub-population independently in order to generate a wide variety of network architectures. During breeding 2-hidden layer architectures, a constraint-based nearest neighbor search algorithm is proposed to find the nearest neighbors of the offspring population generated by mutation. The results showed that for LOCA detection, the GA-optimised network outperformed a random search, an exhaustive search and a RBF kernel support vector regression (SVR) in terms of generalization performance. For the skillcraft dataset of the UCI machine learning repository, the GA-optimised network has a similar performance to the RBF kernel SVR and outperformed the other approaches

Hidden connections: the link between board gender diversity and corporate social performance

This study examines whether and how female board directors may affect corporate social performance (CSP) by drawing on social role theory and feminist ethics literature. The empirical analysis, based on a sample of 126 firms drawn from the S&P500 group of companies over a five-year period, suggests that board gender diversity (BGD) significantly affects corporate social performance. However, this impact depends on the social performance metric under investigation. In particular, more gender diverse boards exert stronger influence on CSP metrics focusing on ‘negative’ business practices, such as the ‘concerns’ dimension of the Kinder Lydenberg Domini, Inc. (KLD) ratings . This is because such CSP ratings have the potential to induce higher levels of ‘empathic caring’, which strongly appeals to female directors. Hence, this study reveals further hidden connections in the BGD-CSP link which have important implications for managers, nongovernmental organisations and socially responsible investors