Assessment of Surface Roughness in Milling of Beech Using a Response Surface Methodology and an Adaptive Network-Based Fuzzy Inference System

Zhu, Zhi‐Biao; Dong, Jiancheng; Wu, Zhanwen; Xu, Wei; Yu, Yingyue; Guo, Xiaoguang; Wang, Xiaodong

doi:10.3390/machines10070567

Cited by 21 publications

(12 citation statements)

References 20 publications

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“…The third step is to model rainfall data using the ANFIS method. ANFIS functionally has almost the same architecture as the fuzzy rule base model and has almost the same construction as a neural network that contains radial functions (Zhu et al, 2022). A linear combination of radial basis functions of input and neuron parameters is the output of this network.…”

Section: Data Pre-processingmentioning

confidence: 99%

Rainfall Forecasting Using an Adaptive Neuro-Fuzzy Inference System with a Grid Partitioning Approach to Mitigating Flood Disasters

Fauzi,

Erlinda,

Arum

2024

JTAM

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Hydrometeorological disasters are one of the disasters that often occur in big cities like Semarang. Hydrometeorological disasters that often occur are floods caused by high-intensity rainfall in the area. Early mitigation needs to be done by knowing about future rain. Rainfall data in Semarang City fluctuates, so the Adaptive Neuro-Fuzzy Inference System (ANFIS) method approach is very appropriate. This research will use the Grid Partitioning (GP) approach to produce more accurate forecasting. The data used in this research is daily rainfall observation data from the Meteorology Climatology Geophysics Agency (BMKG). The membership functions used are Gaussian and Generalized Bell. The two membership functions will be compared based on the RMSE and MAPE values to get the best one. The data used in this research is daily rainfall data. Rainfall in Semarang City every month experiences anomalies, which can result in flood disasters. The ANFIS-GP method with a Gaussian membership function is the best, with an RMSE value of 0.0898 and a MAPE of 5.2911. Based on the forecast results for the next thirty days, a rainfall anomaly of 102.53 mm on the thirtieth day could cause a flood disaster.

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Section: Data Pre-processingmentioning

confidence: 99%

Rainfall Forecasting Using an Adaptive Neuro-Fuzzy Inference System with a Grid Partitioning Approach to Mitigating Flood Disasters

Fauzi,

Erlinda,

Arum

2024

JTAM

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“…Response surface methodology (RSM) [20] was adopted in this work, which was used to develop a mathematical model and determine the effect of processing parameters and their interactions on the MOE. Table 1 is the experimental design obtained by Design-Expert software (Version 12, Stat-Ease Inc., USA) [21].…”

Section: Experimental Designmentioning

confidence: 99%

Investigation on Modulus of Elasticity of Badminton String by Response Surface Methodology

Feng

2022

Advances in Materials Science and Engineering

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Modulus of elasticity (MOE) is one of the important indexes to evaluate the performance of badminton string. In this work, a series of tensile testing were performed to explore the changes in MOE at different temperature, humidity, and tensile rate. Based on the experimental results, an MOE model for badminton string was developed by using response surface methodology. Meanwhile, the significant contribution of each variable and two-factor interactions on MOE were investigated by analysis of variance. The special aim of this work was to determine the optimal processing parameters for maximum MOE for the higher performance of badminton string, and those processing parameters are temperature of 10.7°C, humidity of 0.19%, and tensile rate of 59.98 mm/min, which were propped to be adopted for the actual use of badminton string.

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“…Response surface methodology is a method integrating experimental design and mathematical modeling [13]. The functional relationship between the factors and results in the global range is regressed and fitted based on the representative local points [14].…”

Section: Introductionmentioning

confidence: 99%

Testing and modeling for the tensile strength of nylon badminton string at different processing conditions

2023

Materialwissenschaft Werkst

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Nylon is a thermoplastic engineering material widely used in several applications. But to increase the application of nylon in sports, the focus of this work was to optimize the tensile strength of nylon for badminton string. In particular, the testing conditions (temperature, relative humidity and tensile rate) were investigated. The results obtained showed that increasing the processing temperature and humidity both had a negative effect on tensile strength, while increasing the tensile rate had a positive effect. Then, a mathematical model to predict the tensile strength was established by using a response surface methodology and the optimal conditions were verified to validate the parameters. Furthermore, an analysis of variance was used to determine the significant effect of each term on the final response. Based on the results obtained, it was found that the optimum processing temperature is 2.9 °C with a relative humidity of 0 % when the tensile rate is 60 mm/min.

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Assessment of Surface Roughness in Milling of Beech Using a Response Surface Methodology and an Adaptive Network-Based Fuzzy Inference System

Cited by 21 publications

References 20 publications

Rainfall Forecasting Using an Adaptive Neuro-Fuzzy Inference System with a Grid Partitioning Approach to Mitigating Flood Disasters

Rainfall Forecasting Using an Adaptive Neuro-Fuzzy Inference System with a Grid Partitioning Approach to Mitigating Flood Disasters

Investigation on Modulus of Elasticity of Badminton String by Response Surface Methodology

Testing and modeling for the tensile strength of nylon badminton string at different processing conditions

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