Ram et al. [14] explained the application of neural network in the area of LFC issues. The development of AGC schemes using ANN and fuzzy set theory to utilize the novel aspects of both in single and hybrid AGC system design for power systems has also been mooted by researchers [127]. ...
where\(w_{i,j}\)denotes the neural network weight between\(input_i\)and\(output_j\)and E(.) is the expectation operator taken over time interval [t, t + L]. For each training step of the neural network,e, gradient descent is applied for the optimization of the weights as in Eq....
In this method, a linear model is constructed around the instance to be explained, and the coefficients are interpreted as the significance of the features. However, this approach is seen as an indirect means of generating explanations as it only focusses on the individual contribution of a ...
The features of MO used jointly with the direct computational graph’s structure in the neural network allowed formulating the fuel design problem to solve it using a standard optimization technique. Here, full-scope and greedy search methods were proposed to identify suitable mixtures in the chemica...
All depicted sub-ANNs represent fully connected feed-forward ANNs associated with their illustrated in- and outputs and are explained in detail in Appendix A. CANNs accept as an input strain data in form of the Cauchy-Green tensor C as well as (optionally) also non-kinematic data in the ...
justified by humans2. This ‘explainability’ phenomenon limits the usage of ML models in critical real-world applications (e.g., law or traffic management) since the context of a decision is hard to be justified and explained to the end-users. Our proposed social network analysis-based ...
AI tools and services are evolving at a rapid rate. Current innovations can be traced back to the 2012 AlexNet neural network, which ushered in a new era of high-performance AI built on GPUs and large data sets. The key advancement was the discovery that neural networks could be trained on...
One of the currently existing harmonic restraint differential protection scheme is explained. The need for an artificial neural networks (ANNs) based scheme for identifying inrush and internal fault conditions is described. A feed forward layered network structure based scheme is proposed. The ANN is...
Which is explained by the fact that the number of nodes in the hidden layers defines the complexity and power of the neural network model to delineate underlaying relationships and structures inherent to the database. The number of nodes in the hidden layers should be large enough for the ...
[46]. The most optimized ANN model should be associated with the highest value ofRand the smallest values ofMSEandMAE.Following are the three different error types are considered (a) correlation factor (R) as explained by Eq.7, (b) Mean Squared Error (MSE) as in Eq.8and (c) Mean ...