Related Experiment Video
Updated: Nov 27, 2025
11:15
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
Published on: June 27, 2013
34.2K
Exponential Entropy for Simplified Neutrosophic Sets and Its Application in Decision Making
Jun Ye1, Wenhua Cui1
1Department of Electrical and Information Engineering, Shaoxing University, Shaoxing 312000, China.
Entropy (Basel, Switzerland)
|December 3, 2020
Summary
This study introduces simplified neutrosophic exponential entropy (SNEE) measures for quantifying uncertain information in simplified neutrosophic sets (NSs). These novel measures are validated through comparisons and applied to decision-making problems.
Area of Science:
- Information Theory
- Fuzzy Set Theory
- Neutrosophic Set Theory
Background:
- Entropy is crucial for measuring uncertainty and fuzzy information.
- Simplified neutrosophic sets (NSs) handle incomplete, indeterminate, and inconsistent data.
- Existing entropy measures for NSs have limitations in capturing complex uncertainty.
Purpose of the Study:
- To propose novel exponential entropy measures for simplified neutrosophic sets (SNEE).
- To investigate the properties of these new SNEE measures.
- To demonstrate the effectiveness and applicability of SNEE measures in decision-making.
Main Methods:
- Developed single-valued and interval-valued neutrosophic exponential entropy measures based on fuzzy exponential entropy.
- Analyzed the theoretical properties of the proposed SNEE measures.
- Compared SNEE measures with existing interval-valued NS entropy measures using a numerical example.
- Applied SNEE measures to a multi-attribute decision-making problem in an interval-valued NS environment.
Main Results:
- Introduced and defined simplified neutrosophic exponential entropy (SNEE) measures for both single-valued and interval-valued NSs.
- Established the rationality and effectiveness of SNEE measures through comparative analysis and a numerical example.
- Demonstrated the practical utility of SNEE measures in solving multi-attribute decision-making problems.
Conclusions:
- The proposed SNEE measures effectively quantify uncertain information within simplified neutrosophic sets.
- SNEE measures offer a novel and valuable approach to handling uncertainty in various scientific and engineering domains.
- This work contributes to the theoretical framework of neutrosophic entropy and its practical applications.
Related Concept Videos
02:39Entropy
33.7K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
33.7K
01:18Entropy
3.3K
The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
3.3K
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
185
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
185
01:10Entropy Change in Reversible Processes
3.0K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
3.0K
02:49Second Law of Thermodynamics
26.0K
In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Processes that involve an increase in entropy of the system (ΔS > 0) are very often spontaneous; however, examples to the contrary are plentiful. By expanding consideration of entropy changes to include the surroundings, a significant conclusion regarding the relation between this property and spontaneity may be reached. In thermodynamic models, the...
26.0K
00:53Second Law of Thermodynamics
66.5K
The Second Law of Thermodynamics states that entropy, or the amount of disorder in a system, increases each time energy is transferred or transformed. Each energy transfer results in a certain amount of energy that is lost—usually in the form of heat—that increases the disorder of the surroundings. This can also be demonstrated in a classic food web. Herbivores harvest chemical energy from plants and release heat and carbon dioxide into the environment. Carnivores harvest the...
66.5K