Threshold agent networks (TANs) constitute a discretized modification of threshold (also known as neural) networks that are appropriate for modeling computer simulations. In this p...
When employing a consensus algorithm for state machine replication, should one optimize for the case that all communication links are usually timely, or for fewer timely links? Do...
The transportation planning (TP) is well-known basic network problem. However, for some real-world applications, it is often that the TP model is extended to satisfy other additio...
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
This paper proposes and explains a data treatment technique to improve the accuracy of a neural network estimator in regression problems, where multi-dimensional input data set is...