this study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ann) in broiler chicken. artificial neural networks (anns) are powerful tools for modeling systems in a wide range of applications. the ann model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...

The choice of an input representation for a neural network can have a profound impact on its accuracy in classifying novel instances. However, neural networks are typically computationally expensive to train, making it diicult to test large numbers of alternative representations. This paper introduces fast quality measures for neural network representations, allowing one to quickly and accurate...

We have developed a compact CMOS motiondetection circuit based on a direction-selective neuralnetwork architecture. The circuit consists of asynchronous current-mode digital subcircuits for edge detection and subthreshold analog subcircuits for motiondetection. SPICE and numerical simulations of the network show that the circuit can successfully extract edge lines from incident images and compu...

Machine-learning algorithms aid predictions for complex systems with multiple influencing variables. However, many neural-network related algorithms behave as black boxes in terms of revealing how the prediction of each data record is performed. This drawback limits their ability to provide detailed insights concerning the workings of the underlying system, or to relate predictions to specific ...

Relation classification is associated with many potential applications in the artificial intelligence area. Recent approaches usually leverage neural networks based on structure features such as syntactic or dependency features to solve this problem. However, high-cost structure features make such approaches inconvenient to be directly used. In addition, structure features are probably domainde...

False information and true fact checking it, often co-exist in social networks, each competing to influence people their spread paths. An efficient strategy here contain false is proactively identify if nodes the path are likely endorse (i.e. further it) or refutation (thereby help spreading). In this paper, we propose SCARLET (truSt andCredibility bAsed gRaph neuraLnEtwork model using aTtentio...

A configuration for the Event Task in the Global Decision Phase of the level 2 trigger is proposed, which includes a Neural Network sensitive to the invariant-mass topology of LHC events. The Neural Network and the associated preprocessing can be implemented on the systolic Siemens microprocessor MA16, which has already been used in a neuralnetwork trigger for experiment WA92 at CERN. The corre...