Extended belief rule based system with joint learning for environmental governance cost prediction
نویسندگان
چکیده
منابع مشابه
New model for system behavior prediction based on belief rule based systems
To predict the behavior of a complex engineering system, a model can be built and trained using historical data. However, it may be difficult to obtain a complete and accurate set of data to train the model. Consequently, the model may be incapable of predicting the future behavior of the system with reasonable accuracy. On the other hand, expert knowledge of a qualitative nature and partial hi...
متن کاملPrediction-based Termination Rule for Greedy Learning with Massive Data.
The appearance of massive data has become increasingly common in contemporary scientific research. When sample size n is huge, classical learning methods become computationally costly for the regression purpose. Recently, the orthogonal greedy algorithm (OGA) has been revitalized as an efficient alternative in the context of kernel-based statistical learning. In a learning problem, accurate and...
متن کاملRule-based joint fuzzy and probabilistic networks
One of the important challenges in Graphical models is the problem of dealing with the uncertainties in the problem. Among graphical networks, fuzzy cognitive map is only capable of modeling fuzzy uncertainty and the Bayesian network is only capable of modeling probabilistic uncertainty. In many real issues, we are faced with both fuzzy and probabilistic uncertainties. In these cases, the propo...
متن کاملInference and learning methodology of belief-rule-based expert system for pipeline leak detection
Belief rule based expert systems are an extension of traditional rule based systems and are capable of representing more complicated causal relationships using different types of information with uncertainties. This paper describes how the belief rule based expert systems can be trained and used for pipeline leak detection. Pipeline operations under different conditions are modelled by a belief...
متن کاملSampling based multi-agent joint learning for association rule mining
In order to achieve distributed data mining quickly and efficiently, this paper proposes SMAJL, a model for sampling based multi-agent joint learning which integrates sampling technology and multi-agent argumentation in the field of association rule mining. By sampling, this model can reduce the size of dataset and improve the efficiency of data mining; through joint learning from argumentation...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Ecological Indicators
سال: 2020
ISSN: 1470-160X
DOI: 10.1016/j.ecolind.2020.106070