Thanks to the learnable ability of the neural network, the length of fuzzy rules established in FTSF is expended to an arbitrary length that the expert is not able to handle by the expert system.
Recently, significant public efforts have been directed towards developing low-cost models with capabilities akin to ChatGPT, thereby fostering the growth of open-source conversational models.
Unmanned aerial vehicles (UAVs) are frequently used for inspecting power lines and capturing high-resolution aerial images.
However current research rarely studies the impact of different amounts of instruction data on model performance, especially in the real-world use cases.
This process is studied in Unsupervised domain adaptation (UDA).
PCL detection task is aimed at identifying and categorizing language that is patronizing or condescending towards vulnerable communities in the general media. Compared to other NLP tasks of paragraph classification, the negative language presented in the PCL detection task is usually more implicit and subtle to be recognized, making the performance of common text-classification approaches disappointed.
In particular, based on the gravity model, a series of improved gravity models are proposed to find vital nodes better in complex networks.
Smets proposes the Pignistic Probability Transformation (PPT) as the decision layer in the Transferable Belief Model (TBM), which argues when there is no more information, we have to make a decision using a Probability Mass Function (PMF).
Based on the D-Path and T-Point, a newly accelerated PPA named OPPA-D using the proposed termination criterion is developed which is superior to all other baseline algorithms according to the experiments conducted in this paper.
For $K = 2$ users, we show that the optimized MCCS attains the lower bound and is optimal for caching with uncoded placement.
Information Theory Information Theory
Motivated by the lack of related PPA-based research, a novel framework, the capacitated physarum polycephalum inspired algorithm (CPPA), is proposed to allow capacity constraints toward link flow in the PPA.
However, in many cases, the pairwise comparison matrix is difficult to complete, which obstructs the subsequent operations of the clas- sical AHP.
In that theory, basic probability assignment (BPA) is the basic element for the expression and inference of uncertainty.
The user equilibrium in traffic assignment problem is based on the fact that travelers choose the minimum-cost path between every origin-destination pair and on the assumption that such a behavior will lead to an equilibrium of the traffic network.
In this paper, multiscale probability transformation of basic probability assignment based on the belief function and the plausibility function is proposed, which is a generalization of the pignistic probability transformation.
To demonstrate the efficiency of the proposed method, we apply it to the water distribution networks to estimate the risk of contaminant intrusion.
How to express an expert's or a decision maker's preference for alternatives is an open issue.
A supply chain is a system which moves products from a supplier to customers.
The results of defuzzification at the first step are not coincide with the results of defuzzification at the final step. It seems that the alternative is to defuzzification in the final step in fuzzy DEMATEL.
Parameter estimation based on uncertain data represented as belief structures is one of the latest problems in the Dempster-Shafer theory.
When the edge weight changes, the proposed algorithm can recognize the affected vertices and reconstruct them spontaneously.
Dempster-Shafer theory (D-S theory) is widely used in decision making under the uncertain environment.
In this note, we argue that the axiomatic requirement of range to the measure of aggregated total uncertainty (ATU) in Dempster-Shafer theory is not reasonable.