Name
Abstract | ||
|---|---|---|
Two types of networks that are useful in developing expert systems are proposed. The probabilistic network can be used for predictive types of expert systems, whereas the fuzzy network is more suitable for expert systems that help in decision-making. In both cases, the expert system can operate in two modes. In the normal mode, rules are given by experts and weights are assigned values. In the learning mode, weights are allowed to vary while the system is fed with examples |
Year | DOI | Venue |
|---|---|---|
1990 | 10.1109/ISMVL.1990.122658 | ISMVL |
Keywords | Field | DocType |
logic circuits,multiple valued neural logic elements,many-valued logics,decision-making,probabilistic network,fuzzy logic,fuzzy network,neural nets,probability,neural networks,normal modes,expert system | Discrete mathematics,Logic gate,Computer science,Fuzzy logic,Expert system,Probabilistic logic,Artificial neural network | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Loke-soo Hsu | 1 | 5 | 3.10 |
| Hoon Heng Teh | 2 | 20 | 3.50 |
| Sing-chai Chan | 3 | 0 | 0.68 |
| Kia-Fock Loe | 4 | 180 | 20.88 |