An Indirect Type-2 Fuzzy Neural Network Optimized by the Grasshopper Algorithm for Vehicle ABS Controller

Amirkhani, Abdollah; Shirzadeh, Masoud; Molaie, Mahdi

doi:10.1109/access.2022.3179700

Cited by 22 publications

(10 citation statements)

References 59 publications

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“…Ashraf et al [25] proposed a non-linear system, IT2 vendor-managed inventory system, and solve it with EKM with particle swarm optimization algorithms. IT2 fuzzy neural networks and grasshopper optimization algorithms were suggested by Amirkhani et al [26] for the development of a vehicle antilock braking system. A robust single fuzzifier IT2 fuzzy C-means clustering method to adopt the interval-valued numbers for the application of land cover segmentation was presented by Wu and Gao [27].…”

Section: A Interval Type-2 Fuzzy Set and Applicationsmentioning

confidence: 99%

A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties

et al. 2023

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Multi-objective reliability-redundancy allocation problem (MORRAP) needs to maximize system reliability and minimize cost, weight, and volume with underlining constraints. In the systems' design and analysis phase, uncertainties can occur from various sources, such as manufacturing variability, environmental conditions, user behavior, etc. To deal with this, we present a generalization of the traditional MORRAP under multiple empirical and ambiguous circumstances, named interval type-2 fuzzy multiobjective reliability redundancy allocation problem (IT2FMORRAP). The newly formulated IT2FMORRAP considers optimizing goals as reliability, cost, and weight for a series-parallel system with interval type-2 fuzzy number. The mathematical formulation is established under which the proposed IT2FMORRAP model reduces to T1FMORRAP (type-1 fuzzy MORRAP), IVMORRAP (interval-valued MORRAP), and classical MORRAP. An Enhanced Karnik-Mendel and NSGA-II algorithm-based solving strategy is developed for the proposed IT2FMORRAP. The real-world dataset is considered to demonstrate the efficacy of the solution method for the proposed problem. A Kmean clustering technique identifies the best solution sets from the knee region of the generated Pareto fronts. An experimental study on commonly used performance metrics reveals that IT2FMORRAP performs significantly better than T1FMORRAP and crisp MORRAP. Further, the statistical analysis also confirms the hypothesis established in the empirical research. Finally, a comparative performance study has been conducted with notable state-of-the-art papers from the literature to encounter an appropriate establishment for the proposed work in the domain.

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Section: A Interval Type-2 Fuzzy Set and Applicationsmentioning

confidence: 99%

A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties

et al. 2023

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“…For those cities that have rich freshwater resources but can't fully develop and use them, it will undoubtedly increase the difficulty and cost of exploitation. On the contrary, if these lands can be used as the basis to develop the marine economy, it will bring them more and more benefits and better social benefits, as well as greater benefits and income for the country [11][12].…”

Section: Relationship Between Marine Resources Growth and Marine Economymentioning

confidence: 99%

Relationship between Marine Resources growth and Marine Economy Based on Neural Network

2022

FOE

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With the rapid growth of China's economy, people pay more and more attention to marine resources. In the process of growth and utilization, how to deal with the relationship with the marine ecological environment is also a great challenge for us. In this paper, the domestic and foreign research and analysis on protecting the marine environment, carrying out large-scale marine engineering activities and promoting sustainable fishery production are carried out, and classified and summarized. Through the establishment of models to predict the factors affecting the coastline of the coastal seabed zone and their change rules in different stages, according to the historical data of marine resources, artificial neural networks(NN) are constructed using NN algorithms to study the regional water and soil conservation planning and growth measures based on the marine ecological environment. Finally, the model is simulated and tested. The test results show that the marine resource growth model based on neural algorithm has short data processing time and low delay time, which indicates that the algorithm can meet the operational requirements of the marine resource model.

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“…The intercooling cycle gas turbine is to install an intercooler between the low-pressure compressor and the high-pressure compressor to reduce the compression power consumption of the high-pressure compressor by reducing the gas temperature. The HP coal-fired generator set of indirect cooling cycle machine is two-stage cooling, with simple structure and high unit efficiency [9][10].…”

Section: Intercooled (Regenerative) Cycle Gas Turbinementioning

confidence: 99%

Dynamic Performance Analysis of Gas Turbine with Intermediate Cooling and Regenerative Based on Neural Network Algorithm

2022

KME

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Gas turbine is one of the most important large-scale equipment power plants at present, which has been widely used in the industrial field. Mechanical performance test is a very important parameter for gas turbine. Neural network algorithm can play a great role in system data processing and monitoring. Therefore, in order to observe the dynamic performance of gas turbine, neural network is used to study the data changes related to intermediate cooling and regeneration of gas turbine. This paper mainly uses the experimental method to compare, control the variable of pressure ratio, and analyze its dynamic performance through computer group efficiency, fuel consumption rate and the quality of carbon dioxide and oxygen. The experimental results show that, under rated load, the unit operates with variable pressure ratio. When the pressure ratio is less than 11, if efficiency is required, the unit power can be kept basically constant by changing the fuel quality.

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An Indirect Type-2 Fuzzy Neural Network Optimized by the Grasshopper Algorithm for Vehicle ABS Controller

Cited by 22 publications

References 59 publications

A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties

A Generalized Multiobjective Reliability Redundancy Allocation With Uncertainties

Relationship between Marine Resources growth and Marine Economy Based on Neural Network

Dynamic Performance Analysis of Gas Turbine with Intermediate Cooling and Regenerative Based on Neural Network Algorithm

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