D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 44 Citations 6,209 146 World Ranking 3674 National Ranking 339

Overview

What is he best known for?

The fields of study he is best known for:

  • Algorithm
  • Artificial intelligence
  • Programming language

His scientific interests lie mostly in Theoretical computer science, Membrane computing, P system, Algorithm and Universality. The various areas that Linqiang Pan examines in his Theoretical computer science study include Turing machine, Bio-inspired computing, Artificial intelligence and Spiking neural network. His Membrane computing study integrates concerns from other disciplines, such as Feature, Computational complexity theory, Class, Cell separation and P versus NP problem.

P system and Discrete mathematics are commonly linked in his work. His work in the fields of Algorithm, such as Time complexity, Computable function and Computation, intersects with other areas such as Workspace. His Computation study combines topics from a wide range of disciplines, such as Bounded function and Regular language.

His most cited work include:

  • Asynchronous spiking neural P systems with local synchronization (149 citations)
  • Spiking Neural P Systems with Anti-Spikes (123 citations)
  • On the Universality of Axon P Systems (111 citations)

What are the main themes of his work throughout his whole career to date?

Linqiang Pan spends much of his time researching Membrane computing, Theoretical computer science, P system, Algorithm and Computation. His Membrane computing research is multidisciplinary, incorporating elements of Discrete mathematics, Spiking neural network, Bio-inspired computing and Topology. In his research on the topic of Theoretical computer science, Regular expression is strongly related with Turing machine.

His work in P system addresses subjects such as Membrane, which are connected to disciplines such as Division. His Algorithm study frequently intersects with other fields, such as Mathematical optimization. His Computation research is multidisciplinary, incorporating perspectives in Natural number, Turing, Neuron, Set and Biological system.

He most often published in these fields:

  • Membrane computing (45.41%)
  • Theoretical computer science (27.51%)
  • P system (28.82%)

What were the highlights of his more recent work (between 2017-2021)?

  • Membrane computing (45.41%)
  • Topology (21.40%)
  • Computation (21.40%)

In recent papers he was focusing on the following fields of study:

His main research concerns Membrane computing, Topology, Computation, Turing and Bio-inspired computing. His work carried out in the field of Membrane computing brings together such families of science as Sat problem, Time complexity, P versus NP problem, Class and Spiking neural network. The concepts of his Time complexity study are interwoven with issues in Theoretical computer science, Division and Type.

His studies deal with areas such as Algorithm, Regular expression and Natural number as well as Spiking neural network. His study in Topology is interdisciplinary in nature, drawing from both Set, P system and Membrane. His Computation research integrates issues from Class and Neuron.

Between 2017 and 2021, his most popular works were:

  • A Classification-Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization (86 citations)
  • Simplified and yet Turing universal spiking neural P systems with communication on request (55 citations)
  • Simplified and yet Turing universal spiking neural P systems with communication on request (55 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Algorithm
  • Programming language

His scientific interests lie mostly in Bio-inspired computing, Turing, Spiking neural network, Artificial neural network and Membrane computing. While working on this project, he studies both Turing and Universality. He interconnects Natural number, P system and Regular expression in the investigation of issues within Spiking neural network.

His Artificial neural network research includes themes of Evolutionary algorithm and Mathematical optimization. Linqiang Pan has researched Membrane computing in several fields, including Distribution, Representation, Gradient descent, Function and Variable. His Small number research includes themes of Evolutionary computation, Optimization problem, Set, Multiobjective optimization problem and Linear programming.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Asynchronous spiking neural P systems with local synchronization

Tao Song;Linqiang Pan;Gheorghe Pun.
Information Sciences (2013)

241 Citations

Spiking Neural P Systems with Anti-Spikes

Linqiang Pan;Gheorghe Paun.
International Journal of Computers Communications & Control (2009)

201 Citations

Computational complexity of tissue-like P systems

Linqiang Pan;Mario J. Pérez-Jiménez.
Journal of Complexity (2010)

168 Citations

On the Universality of Axon P Systems

Xingyi Zhang;Linqiang Pan;Andrei Paun.
IEEE Transactions on Neural Networks (2015)

167 Citations

P systems with minimal parallelism

Gabriel Ciobanu;Linqiang Pan;Gheorghe Pun;Mario J. Pérez-Jiménez.
Theoretical Computer Science (2007)

144 Citations

Deterministic solutions to QSAT and Q3SAT by spiking neural P systems with pre-computed resources

Tseren-Onolt Ishdorj;Alberto Leporati;Linqiang Pan;Xiangxiang Zeng.
Theoretical Computer Science (2010)

142 Citations

Solving a PSPACE-complete problem by recognizing P systems with restricted active membranes

Artiom Alhazov;Carlos Martín-Vide;Linqiang Pan.
Fundamenta Informaticae (2003)

139 Citations

Spiking neural p systems with weights

Jun Wang;Hendrik Jan Hoogeboom;Linqiang Pan;Gheorghe Păun.
Neural Computation (2010)

138 Citations

Spiking Neural P Systems With Rules on Synapses Working in Maximum Spiking Strategy

Tao Song;Linqiang Pan.
IEEE Transactions on Nanobioscience (2015)

127 Citations

Normal Forms of Spiking Neural P Systems With Anti-Spikes

Tao Song;Linqiang Pan;Jun Wang;I. Venkat.
IEEE Transactions on Nanobioscience (2012)

123 Citations

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Best Scientists Citing Linqiang Pan

Mario J. Pérez-Jiménez

Mario J. Pérez-Jiménez

University of Seville

Publications: 79

Xiangxiang Zeng

Xiangxiang Zeng

Hunan University

Publications: 32

Giancarlo Mauri

Giancarlo Mauri

University of Milano-Bicocca

Publications: 22

Quan Zou

Quan Zou

University of Electronic Science and Technology of China

Publications: 19

Yaochu Jin

Yaochu Jin

University of Surrey

Publications: 17

Qiang Zhang

Qiang Zhang

Dalian University of Technology

Publications: 16

Xingyi Zhang

Xingyi Zhang

Anhui University

Publications: 15

Fang-Xiang Wu

Fang-Xiang Wu

University of Saskatchewan

Publications: 12

Xun Wang

Xun Wang

Tsinghua University

Publications: 10

Ferrante Neri

Ferrante Neri

University of Nottingham

Publications: 9

Peng Shi

Peng Shi

University of Adelaide

Publications: 7

Min Li

Min Li

Central South University

Publications: 7

Jianxin Wang

Jianxin Wang

Central South University

Publications: 6

Humberto González-Díaz

Humberto González-Díaz

University of the Basque Country

Publications: 6

Luonan Chen

Luonan Chen

Chinese Academy of Sciences

Publications: 6

Gheorghe Paun

Gheorghe Paun

Romanian Academy

Publications: 5

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