In the structure of ANFIS, there are two different parameter groups: premise and consequence. Training ANFIS means determination of these parameters using an optimization algorithm. In the first ANFIS model developed by Jang, a hybrid learning approach was proposed for training. In this approach, while premise parameters are determined by using gradient descent (GD), consequence parameters are found out with least squares estimation (LSE) method. Since ANFIS has been developed, it is used in modelling and identification of numerous systems and successful results have been achieved. The selection of optimization method utilized in training is very important to get effective results with ANFIS. It is seen that derivate based (GD, LSE etc.) and non-derivative based (heuristic algorithms such us GA, PSO, ABC etc.) algorithms are used in ANFIS training. Nevertheless, it has been observed that there is a trend toward heuristic based ANFIS training algorithms for better performance recently. At the same time, it seems to be proposed in derivative and heuristic based hybrid algorithms. Within the scope of this study, the heuristic and hybrid approaches utilized in ANFIS training are examined in order to guide researchers in their study. In addition, the final status in ANFIS training is evaluated and it is aimed to shed light on further studies related to ANFIS training.

Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey

In this paper, we propose a novel algorithm-parallel adaptive quantum genetic algorithm-which can rapidly determine the minimum control nodes of arbitrary networks with both control nodes and state nodes. The corresponding network can be fully controlled with the obtained control scheme. We transformed the network controllability issue into a combinational optimization problem based on the Popov-Belevitch-Hautus rank condition. A set of canonical networks and a list of real-world networks were experimented. Comparison results demonstrated that the algorithm was more ideal to optimize the controllability of networks, especially those larger-size networks. We demonstrated subsequently that there were links between the optimal control nodes and some network statistical characteristics. The proposed algorithm provides an effective approach to improve the controllability optimization of large networks or even extra-large networks with hundreds of thousands nodes.

/pdf/a-parallel-adaptive-quantum-genetic-algorithm-for-the-18quwyef8c.pdf

A parallel adaptive quantum genetic algorithm for the controllability of arbitrary networks.

To evaluate the practical ability of crews during the navigation of an inward-port single ship, a track evaluation model was developed on a planar forward normal cloud chart under sample information based on the forward normal and the backward normal cloud generator. Since the track sampling cloud may be too divergent, a track belt division method based on the contributions of normal cloud drops was proposed. Combining the track evaluation model with the track belt division method, a comprehensive track evaluation scheme of the local sampling cloud based on sampling information was established. The results of an example of M.V. DAQING 257 unloaded into Dalian Port demonstrated the effectiveness of the model and showed its consistency with expert evaluation results based on subjective information. The proposed uncertainty evaluation model provides a new approach for intelligent evaluation under sample information.

Towards an uncertainty evaluation model for marine track considering local sampling cloud and sample information

Combined with quantum computing and genetic algorithm, quantum genetic algorithm (QGA) shows considerable ability of parallelism. Experiments have shown that QGA performs quite well on TSP, job shop problem and some other typical combinatorial optimization problems. The other problems like nutritional diet which can be transformed into specific combinational optimization problem also can be solved through QGA smoothly. This paper sums up the main points of QGA for general combinatorial optimization problems. These points such as modeling of the problem, qubit decoding and rotation strategy are useful to enhance the convergence speed of QGA and avoid premature at the same time.

A Survey of Quantum Genetic Algorithm for Combinatorial Optimization Problems

In order to verify the similarity of the servo system of the main-fin and the flap-fin of the established fin-flap control physical simulation system in the drive way with the prototype system, the method of equivalence analysis based on the principle of similarity is proposed in this paper. In order to better determine the weights of each subsystem, the consistency correction method of the judgment matrix is studied combined with hierarchical analysis principle. Finally, the main-fin / flap-fin servo system is taken for example to analyze the equivalence of flap-fin control of physical simulation system, and the proposed method in this paper is proved to be feasible.

Ship Flap-Fin Equivalence Analysis Based on AHP

Currently, in alpine region, the main way of heating for the greenhouse is coal heating in winter. This heating method has many drawbacks. During the winter heating period greenhouse will consume large amounts of coal and produce large amounts of pollution. In addition, coal heating also relates to the issue of fire safety, there is security risk. Therefore, using new energy for heating to instead of coal fire heating has a very important significance. Wind and solar energy have the great application prospects and both of them are new clean energy resources which the technology is more mature. In this paper, the design of the greenhouse system use renewable and clean energy as the primary energy supply. The design uses “wind and solar hybrid system” to provide energy for the greenhouse. The system takes efficient energy storage and conversion device for heating the air and soil in the greenhouse, system can meet its own needs and ensure the temperature is appropriate for growth of plants in the greenhouse. Besides, the system can run without other energy supplement in the whole operation cycle. At the same time, this greenhouse system does not produce any harmful pollutants, so that it achieves the full-year zero-emission operation.

The Design for Zero Emission Greenhouse System

in this paper, the concepts of modelling, simulation, verification and validation are described in order to analyse their necessities in electric ship propulsion system simulation. Traditional verification and validation methods are outlined before a new method based on expert theory and verification and validation methods of software testing is proposed to verify if the simulation program meets customers needs and respective software protocols, according to the characteristics of electric ship propulsion system.

Verification, Validation and Accreditation of Ship Electric Propulsion Simulation System

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Bing Li

Author Tools

Chat about Author

Papers

A Survey of Quantum Genetic Algorithm for Combinatorial Optimization Problems

Ship Flap-Fin Equivalence Analysis Based on AHP

The Design for Zero Emission Greenhouse System

Verification, Validation and Accreditation of Ship Electric Propulsion Simulation System