We investigate storage capacity of two types of fully connected layered neural networks with sparse coding when binary patterns are embedded into the networks by a Hebbian learning rule. One of them is a layered network, in which a transfer function of even layers is different from that of odd...

We investigate storage capacity of a fully connected layered neural network with Q(⩾2)-states clock neurons, including Q=∞ (corresponding to oscillatory neurons) and with intra-layer connections, where random Q-values patterns are embedded into the network by the Hebbian learning rule. We...

Selection of a storage capacity for the design ofa river reservoir is made traditionally by the Rippl masscurve method or the sequent-peak algorithm. Both methods offera single value of storage capacity to a water resourcesengineer. Synthetic hydrology approach by which long syntheticflow data...

The purpose of this paper is to examine water use estimation in hydel and thermal electric power plants in selected regions i.e. Coastal, Rayalaseema and Telangana regions of Andhra Pradesh. The study primarily focuses on the realistic fundamental premise thatthermal electric and hydro electric...