An Entropy Measurement Method of Quantum Information System under Uncertain Environment

AbstractThis article illustrates an application of a hybrid optimization approach for the determination of the optimum machining parameters to achieve better productivity without negotiating the qualities and accuracy of the EDMed components. A synergy of Response Surface Methodology (RSM), Grey Relational Analysis (GRA) coupled with Energy measurement method has been applied that maximises Material Removal Rate (MRR) and simultaneously minimises Tool Wear Rate (TWR) & Radial overcut or Gap(G) during Electrical Discharge Machining (EDM) of AISI D2 Tool steel. The input process parameters considered are pulse current (Ip), pulse duration (Ton), duty cycle (Tau) and discharge voltage (V). A face centered Central Composite Design (CCD) has been adopted for conducting the experiments. The designed experimental results were used in grey relational analysis, and the weights of the quality characteristics were decided by utilizing the entropy measurement method. The significant parameters are obtained by accomplishing Analysis of Variance (ANOVA). Based on the RSM results, it is found that the grey relational grades are considerably influenced by the machining parameters and some of their interactions. Ip is found to be most influencing parameter with 35.02%contribution followed by interaction of Ip×Ton and Tau with 21.74%and 17.73%contribution respectively. The coefficient of determination (R2) is found to be 91.1%which is quite satisfactory. These results furnish useful information to control the responses and ensure the high productivity and accuracy of the component. This method is simple with easy operability, and moreover the results have also been confirmed by running the confirmation tests.

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Information structures and entropy measurement for a fuzzy probabilistic information system

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-210149 ◽

2021 ◽

pp. 1-19

Author(s):

Yanling He ◽

Chunji Yao

Keyword(s):

Information System ◽

Information Structure ◽

Granular Computing ◽

Basic Structure ◽

Fuzzy Relations ◽

Information Structures ◽

Inclusion Degree ◽

Probabilistic Information ◽

Entropy Measurement ◽

Types Of Information

An information system (IS), an important model in the field of artificial intelligence, takes information structure as the basic structure. A fuzzy probabilistic information system (FPIS) is the combination of some fuzzy relations in the same universe that satisfy probability distribution. A FPIS as an IS with fuzzy relations includes three types of uncertainties (i.e., roughness, fuzziness and probability). This paper studies information structures in a FPIS from the perspective of granular computing (GrC). Firstly, two types of information structures in a FPIS are defined by set vectors. Then, equality, dependence and independence between information structures in a FPIS are proposed, and they are depicted by means of the inclusion degree. Next, information distance between information structures in a FPIS is presented. Finally, entropy measurement for a FPIS is investigated based on the proposed information structures. These results may be helpful for understanding the nature of structures and uncertainty in a FPIS.

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Research and development of a quantum computing system as an information process.

Informatization and communication ◽

10.34219/2078-8320-2021-12-5-86-89 ◽

2021 ◽

Vol 5 ◽

Author(s):

V.S. Potapov ◽

◽

S.M. Gushansky

Keyword(s):

Information System ◽

Quantum Computing ◽

Quantum Information ◽

Computing System ◽

Software Implementation ◽

Quantum Circuits ◽

Quantum Gates ◽

Information Process ◽

Component Structure ◽

The Past

Over the past few decades, there has been a significant breakthrough in the field of quantum computing. Research is attracting growing interest, which has recently led to the development of quantum information systems prototypes and methods for their development. The paper describes the characteristics of the information system as an object of architecture and the representation of quantum gates using quantum circuits. A functional-component structure of a quantum information system has been built and a software implementation of a quantum information system has been made on its basis.

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ENERGY DISSIPATION IN A HOUTAPPEL–ISING QUANTUM INFORMATION PROCESSOR WITH HIERARCHICAL NOISE

International Journal of Quantum Information ◽

10.1142/s0219749911007988 ◽

2011 ◽

Vol 09 (05) ◽

pp. 1307-1317

Author(s):

M. ÁVILA ◽

M. MARTÍNEZ ◽

F. MONROY ◽

A. BARRAGÁN

Keyword(s):

Nuclear Magnetic Resonance ◽

Information System ◽

Quantum Information ◽

Energy Dissipation ◽

Magnetic Resonance ◽

Hierarchical Interaction ◽

One Step ◽

Landauer’S Principle ◽

Theoretical Results ◽

Nuclear Magnetic

By assuming a hierarchical interaction with the environments within the Houtappel approximation, decoherence effects on a Quantum Information System (QIS) are studied. In order to avoid a harmful "always on" effect it is assumed that such interaction happens in a single one step. As a result the decoherence times are quantized and inversely proportional to the strength of the couplings of the QIS with the environment. The decoherence is manifested as a liberated heat by the QIS. By Landauer's principle this effect erases the information. Our theoretical results are applied to three different Nuclear Magnetic Resonance systems. Bounds to the probability of erasing the information are imposed for these systems.

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Reduction in a fuzzy probabilistic information system

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-202783 ◽

2021 ◽

pp. 1-17

Author(s):

Damei Luo ◽

Zhaowen Li ◽

Liangdong Qu

Keyword(s):

Information System ◽

Probability Distribution ◽

Set Theory ◽

Rough Set ◽

Rough Set Theory ◽

Mathematical Tool ◽

Fuzzy Relations ◽

Probabilistic Information ◽

Entropy Measurement ◽

The Universe

An information system (IS) is an important mathematical tool for artificial intelligence. A fuzzy probabilistic information system (FPIS), the combination of some fuzzy relations in the same universe which satisfies the probability distribution, can be seen as an IS with fuzzy relations. A FPIS overcomes the shortcoming that rough set theory assumes elements in the universe with equal probability and leads to lose some useful information. This paper integrates the probability distribution into the fuzzy relations in a FPIS and studies its reduction. Firstly, the concept of a FPIS is introduced and its reduction is proposed. Then, the fuzzy relations in a FPIS are divided into three categories (P-necessary, P-relatively necessary and P-unnecessary fuzzy relations) according to their importance. Next, entropy measurement for a FPIS is investigated. Moreover, some reduction algorithms are constructed. Finally, an example is given to verify the effectiveness of these proposed algorithms.

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