Artificial neural network representations for hierarchical preference structures
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Publication:1360135
DOI10.1016/S0305-0548(96)00021-4zbMath0876.90007WikidataQ57570795 ScholiaQ57570795MaRDI QIDQ1360135
Antonie Stam, Minghe Sun, Marc N. Haines
Publication date: 15 July 1997
Published in: Computers \& Operations Research (Search for Journal in Brave)
analytic hierarchy processpreference ratingsfeed-forward neural networkartificial neural network formulationsfuzzy ratio-scale preference judgmentsmodified Hopfield network
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Uses Software
Cites Work
- Self-organization and associative memory
- Introduction to computation and learning in artificial neural networks
- ``Neural computation of decisions in optimization problems
- Consistent weights for judgements matrices on the relative importance of alternatives
- A feedforward neural network for multiple criteria decision making
- A scaling method for priorities in hierarchical structures
- A comparison of two methods for determining the weights of belonging to fuzzy sets
- A multicriteria evaluation of methods for obtaining weights from ratio- scale matrices
- Preference programming through approximate ratio comparisons
- Starting rules for incomplete comparisons in the analytic hierarchy process
- Consistency prediction for incomplete AHP matrices
- Preference Assessment by Imprecise Ratio Statements
- Feedforward Artificial Neural Networks for Solving Discrete Multiple Criteria Decision Making Problems
- Neural networks and physical systems with emergent collective computational abilities.
- Neurons with graded response have collective computational properties like those of two-state neurons.
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