Recognizing Affect from Linguistic Information in 3D Continuous Space

We introduce a novel approach for the computation of stable and supported models of normal logic programs in continuous vector spaces by a gradient-based search method. Specifically, the application of the immediate consequence operator of a program reduct can be computed in a vector space. To do this, Herbrand interpretations of a propositional program are embedded as 0-1 vectors in $\mathbb{R}^N$ and program reducts are represented as matrices in $\mathbb{R}^{N \times N}$. Using these representations we prove that the underlying semantics of a normal logic program is captured through matrix multiplication and a differentiable operation. As supported and stable models of a normal logic program can now be seen as fixed points in a continuous space, non-monotonic deduction can be performed using an optimisation process such as Newton's method. We report the results of several experiments using synthetically generated programs that demonstrate the feasibility of the approach and highlight how different parameter values can affect the behaviour of the system.

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Experience of Creation in Ukraine of the System of Continuous Space Education: School, University, Enterprise

10.2514/6.iac-03-p.p.09 ◽

2003 ◽

Author(s):

Olexandr Novykov

Keyword(s):

Continuous Space ◽

Education School

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MESHFREEFLOWNET: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework

SC20: International Conference for High Performance Computing, Networking, Storage and Analysis ◽

10.1109/sc41405.2020.00013 ◽

2020 ◽

Author(s):

Chiyu lMaxr Jiang ◽

Soheil Esmaeilzadeh ◽

Kamyar Azizzadenesheli ◽

Karthik Kashinath ◽

Mustafa Mustafa ◽

...

Keyword(s):

Super Resolution ◽

Space Time ◽

Continuous Space

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Extended VIKOR-QUALIFLEX Method Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Information for Multiple Attribute Decision-Making with Unknown Attribute Weight

Mathematics ◽

10.3390/math9010037 ◽

2020 ◽

Vol 9 (1) ◽

pp. 37

Author(s):

Ye Li ◽

Yisheng Liu

Keyword(s):

Decision Making ◽

Qualitative Evaluation ◽

Multiple Attribute Decision Making ◽

Two Dimensional ◽

Linguistic Variables ◽

Linguistic Information ◽

Attribute Weight ◽

Model Based ◽

Subjective Weight ◽

Multiple Attribute

Considering the advantages of trapezoid fuzzy two-dimensional linguistic variables (TrF2DLVs), which can not only accurately describe the qualitative evaluation but also use qualitative linguistic variables (LVs) to describe the confidence level of this evaluation in the second dimension, this paper proposes a novel method based on trapezoidal fuzzy two-dimensional linguistic information to solve multiple attribute decision-making (MADM) problems with unknown attribute weight. First, a combination weight model is constructed, which covers a subjective weight determination model based on the proposed trapezoidal fuzzy two-dimensional linguistic best-worst method (TrF2DL-BWM) and an objective weight determination model based on the proposed CRITIC method. Then, in order to accurately rank the alternatives, an extended VIKOR-QUALIFLEX method is proposed, which can measure the concordance index of each ranking combination by means of group utility and individual maximum regret value of each evaluation alternative. Finally, a practical problem of lean management assessment for industrial residential projects is solved by the proposed method, and the effectiveness and advantages of the method are demonstrated by comparative analysis and discussion.

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