Results 241 to 250 of about 254,846 (297)
Business Strategy and the Environment, EarlyView.ABSTRACT Environmental protection has emerged as a global priority in the contemporary context. As pivotal actors in the transition towards sustainable development, companies play a crucial role through the adoption of environmental innovations. This study investigates how organisational characteristics—specifically geographical location, business ...
Carlos de las Heras‐Rosas +3 more
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Business Strategy and the Environment, EarlyView.ABSTRACT The emerging concept of Hubs for Circularity (H4Cs) presents an opportunity to create collaborative, self‐sustaining regional industrial ecosystems that drive circular economy transitions at scale. However, the operationalisation of H4Cs faces financial, organisational and data‐driven challenges.
Aditya Tripathi +3 more
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Business Strategy and the Environment, EarlyView.ABSTRACT Reaching global net‐zero targets has become an urgent priority as businesses and nations face increasing pressure to reduce greenhouse gas emissions. Achieving carbon neutrality in manufacturing supply chains requires comprehensive systemic changes across business processes.
Vimal K. E. K. +5 more
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Behavioral Sciences &the Law, EarlyView.ABSTRACT As correctional jurisdictions and risk instrument developers look to optimize scoring for specific population needs, an open question remains ‐ which method is optimal. Popular scoring methods range from manual simple scoring approaches (e.g., Burgess) to more complex machine learning algorithms (e.g., random forests).
Danielle J. Rieger +2 more
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Application of Artificial Neural Networks (ANNs) in Wine Technology
Critical Reviews in Food Science and Nutrition, 2013In recent years, neural networks have turned out as a powerful method for numerous practical applications in a wide variety of disciplines. In more practical terms neural networks are one of nonlinear statistical data modeling tools. They can be used to model complex relationships between inputs and outputs or to find patterns in data.
Halil, Baykal, Hatice Kalkan, Yildirim
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Artificial neural networks (ANNs) and modeling of powder flow
International Journal of Pharmaceutics, 2003Effects of micromeritic properties (bulk, tapped and particle density, particle size and shape) on the flow rate through circular orifices are investigated, for three pharmaceutical excipients (Lactose, Emcompress and Starch) separated in four sieve fractions, and are modeled with the help of artificial neural networks (ANNs).
K, Kachrimanis +2 more
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Artificial Neural Networks (ANN)
2007This chapter introduces the basic principles of artificial neural networks (ANN) as computational models that mimic the brain in its main principles. Theyhavebeenused so far to model brain functions, along with solving complex problems of classification, prediction, etc. in all areas of science, engineering, technology and business.
Lubica Benuskova, Nikola Kasabov
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Applications of Artificial Neural Networks (ANNs) in Food Science
Critical Reviews in Food Science and Nutrition, 2007Artificial neural networks (ANNs) have been applied in almost every aspect of food science over the past two decades, although most applications are in the development stage. ANNs are useful tools for food safety and quality analyses, which include modeling of microbial growth and from this predicting food safety, interpreting spectroscopic data, and ...
Yiqun, Huang +2 more
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Design Issues in Artificial Neural Network (ANN)
2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), 2019Artificial Neural Network (ANN) has many variants having vast application spectrum. The important aspect of any ANN system is the optimization of various design parameters in order to get robust performance with good accuracy. However, there is a lack of generalized rules with respect to various design issues of ANN.
Nidhi Kanwar +2 more
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Instability localization with artificial neural networks (ANNs)
Annals of Nuclear Energy, 2002Abstract The aim of this piece of research is to investigate the potential of artificial neural networks (ANNs) for tackling the problem of instability localization. The instability is modeled by a variable strength absorber (point-source) in a two-dimensional bare reactor model with a one neutron-energy group.
T. Tambouratzis, M. Antonopoulos-Domis
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