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Voltage ranking attempts to rank busbar voltage deviations from their normally accepted security margins based on a set of performance indices (PI), without performing a full load flow. Existing methods suffer from either masking effects or long computation time. In this paper, an artificial neural network method is proposed for voltage ranking. Counterpropagation network (CPN) has been employed to overcome the problems listed above. A variety of input features are used with the aim of lowering the dimension of the proposed ANN to make it applicable for large power systems. The method is tested on two example systems, a five‐bus system and a 71‐bus system with very encouraging results.

Artificial intelligence, including expert systems, fuzzy logic, neural networks and genetic algorithms, is increasingly being applied to the solution of a wide range of problems in the monitoring and operation of electricity supply systems. Following the privatization of the Electricity Supply Industry in England and Wales in 1990, there is an overriding commercial incentive for the privatized electricity companies to operate the high voltage transmission networks as economically as possible without compromizing their reliability in a climate of substantial uncertainty as to the generator prices and availabilities that are bid into the pool from day to day and the energy trading contracts that have to be implemented. These circumstances often mean that the transmission and distribution networks must operate close to their defined security limits and still be capable of surviving severe disturbances. Hence artificial intelligence is being applied to the development of online real‐time monitoring systems to assist the electricity supply companies' control room engineers. This paper reviews this field and presents two case studies.

Automatic contingency selection aims to quickly predict the impact of a set of next contingencies on an electric power system without actually performing a full ac load flow. Artificial neural network methods have been employed to overcome the masking effects or slow execution associated with existing methods. However, the large number of input features for the ANN limits its applications to large power systems. In this paper, a novel feature selection method, named the Weak Nodes method, based on a heuristic approach is proposed for an ANN‐based automatic contingency selection for electric power system, especially for the voltage ranking problem. Pre‐contingency state variables of weak nodes in the power system are adopted as input features for the ANN. The method is tested on the 77 busbar NGC derived network by Counter‐propagation Method and it is proved that it reduces the input features for ANN dramatically without losing ranking accuracy.

This study identifies measures to recover economic growth and build sustainable societies and markets in post-COVID-19 scenarios – with a perspective of resilience and adaptability to climate change and massive biodiversity loss. Additionally, this study uncovers the interventions implemented to address economic, environmental and social consequences of past crises based on a systematic literature review. Specifically, this chapter provides answers to the following six questions:

1. What has been done in the past to rebuild social, economic and environmental balance after global crises?

2. Where (geographical region) did the analysis on measures taken concentrate?

3. When have scholars analysed past measures to rebuild business and society after a global crisis?

4. How did the past measures to rebuild business and society after the global crisis take place?

5. Who promotes the measures to rebuild business and society after a global crisis takes place?

6. Why is it important to study the previous literature on past measures to rebuild business and society after a global crisis takes place?

What has been done in the past to rebuild social, economic and environmental balance after global crises?

Where (geographical region) did the analysis on measures taken concentrate?

When have scholars analysed past measures to rebuild business and society after a global crisis?

How did the past measures to rebuild business and society after the global crisis take place?

Who promotes the measures to rebuild business and society after a global crisis takes place?

Why is it important to study the previous literature on past measures to rebuild business and society after a global crisis takes place?

Finally, this chapter identifies future research opportunities to rebuild business and society after the past global crises.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

Heterogeneity in choice models is typically assumed to have a normal distribution in both Bayesian and classical setups. In this paper, we propose a semiparametric Bayesian framework for the analysis of random coefficients discrete choice models that can be applied to both individual as well as aggregate data. Heterogeneity is modeled using a Dirichlet process, which varies with consumers’ characteristics through covariates. We develop a Markov Chain Monte Carlo algorithm for fitting such model, and illustrate the methodology using two different datasets: a household-level panel dataset of peanut butter purchases, and supermarket chain-level data for 31 ready-to-eat breakfast cereal brands.

Mr Macqueen proceeds from a description of the problems which industry and society in general create for those learning and teaching industrial crafts to some useful suggestions for the teacher of craft skills.

This chapter explores social enterprises as an alternative and addition to traditional entrepreneurial ecosystems (EEs). It reviews the substantial social enterprise literature in order to identify the myriad of competing tensions constraining development and success of social EEs in areas of significant poverty and economic deprivation. Following this, the findings of several contemporary and novel studies are discussed. These collectively evidence ways social enterprises are overcoming the seemingly immutable constraints they operate under. In particular, the Social Enterprise Places initiative has been highly effective in supporting the development of flourishing social EEs in many locations in the UK. However, the growth of social enterprises, both in number and economic importance, presents further challenges that social enterprise owners and managers will have to contend with. Consequently, these organisations and their allied ecosystems require continued structural, financial and skills support.