Improving KNN Algorithm Based on Weighted Attributes by Pearson Correlation Coefficient and PSO Fine Tuning

Sinhashthita, Wanarase; Jearanaitanakij, Kietikul

doi:10.1109/incit50588.2020.9310938

Cited by 7 publications

(5 citation statements)

References 13 publications

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“…This study used the Pearson correlation coefficient to analyze the coupling degree of vegetation carbon sequestration density and ex‐situ poverty alleviation and relocation intensity. The Pearson correlation coefficient (Lei et al, 2021; Sinhashthita & Jearanaitanakij, 2020) is widely used to measure the degree of correlation between two variables, and its value interval is [−1, 1]. If the value is greater than zero, then the two vectors are positively correlated.…”

Section: Methodsmentioning

confidence: 99%

Contribution of vegetation restoration to carbon sequestration driven by ex‐situ poverty alleviation and relocation in ecologically fragile areas—Taking Guizhou, China, as a case

et al. 2023

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Vegetation restoration in ecologically fragile areas has a significant carbon sequestration (CS) effect. However, it is usually difficult to achieve quantitative assessment at the regional scale for this part of human activity intervention. The Chinese government's ex‐situ poverty alleviation and relocation (EPAR) project has relocated approximately 10 million people from areas with a fragile ecological environment to urban centralized resettlement, which is a typical case of weakened environmental intervention by human activities (Guizhou Province accounting for approximately 20% of the total relocated population in China). The CS model of vegetation photosynthesis and spatial analysis of geographic information were used to quantify the contribution of human activities to the natural restoration of vegetation CS, based on the data of net primary productivity (NPP) of vegetation from 2000 to 2020. The results show that the implementation of the EPAR project acts as an external force to drive vegetation restoration and CS, which increases the slope of the carbon density change trend (from k = 30.9 to k = 57.41), resulting in an overall carbon density increase of 26.51 tCkm−2. The regional spatial analysis showed that the correlation coefficients between carbon density and relocation intensity in the 5‐year and 10‐year change were r = 0.976 (p < 0.01) and r = 0.949 (p < 0.05), respectively, indicating a significant positive correlation. Based on this, the CS contribution of vegetation in 84 districts in Guizhou Province that implemented EPAR projects was calculated, showing that 79 districts contributed positively, accounting for 94%. The average contribution of CS by vegetation restoration in each district was 0.0556 Tg, and offset CO2 emissions were 0.2059 Tg. The other five districts with a negative contribution to CS were distributed in regions with relatively stable ecosystems and mature forests. This shows that human intervention in the environment changes more significantly in fragile ecological areas.

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Section: Methodsmentioning

confidence: 99%

Contribution of vegetation restoration to carbon sequestration driven by ex‐situ poverty alleviation and relocation in ecologically fragile areas—Taking Guizhou, China, as a case

et al. 2023

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“…Figure 2 (e) shows the speckle patterns after the scattering. Figure 2 (f) shows the phase reconstructed by the U-Net, where the Pearson Correlation Coefficient (PCC) [12] between the reconstructed phase and the real phase is marked below, which is on average above 0.98. This result demonstrates that the U-Net can accurately reconstruct the phase from the speckle pattern even if it is affected by noise and speckle center-shift.…”

Section: Phase Reconstructionmentioning

confidence: 99%

Deep learning based optical orbital angular momentum demultiplexing under high scattering

Liu

Yin²,

Zhang³

2023

International Conference on Optical Technology, Semiconductor Materials, and Devices (OTSMD 2022)

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Optical communication systems based on orbital angular momentum (OAM) theoretically have great potential to increase the channel capacity of the system. When light passes through a high scattering medium, its phase and intensity are affected by scattering, which makes it difficult to demultiplex the OAM modes. In order to alleviate the mode crosstalk caused by scattering, this paper proposes a deep learning based scheme for OAM modes demultiplexing. A simulation model of the optical communication system is built based on the scattering medium transmission matrix theory. The multiplexed OAM beam is transmitted through the system to generate the speckle pattern, matching the incident phase distribution as the data set. Based on this dataset, a U-Net type Deep Neural Networks (DNN) are trained to reconstruct the phase of the light distorted by the scattering medium, thereby the multiplexed OAM modes are identified by a Visual Geometry Group (VGG) type DNN. The simulation results show that at a signal-to-noise ratio (SNR) of (1, 20) dB, the recognition rate of the demultiplexed OAM modes can reach beyond 97%. For grayscale image transmitting via OAM multiplexing under the high scattering, the Pearson correlation between the demultiplexed image and the original image is more than 0.98.

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“…Figure 2 shows a correlation coefficient between -1 and 1 [10]. The formula for calculating the closeness of the relationship between one variable and another (r) can be seen in the following Equation [11]:…”

Section: Mathematical Analysismentioning

confidence: 99%

Correlation coefficient estimation of red chili (Capsicum annuum L) stomatal parameters under shade treatment condition

Putra

Sutiarso

Nugroho

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Stomatal is the most crucial part of plant organs that function as the gas exchange between CO2 and O2 in the environment through diffusion. Optimal stomatal performance can improve the quality of plant growth. This research aimed to determine the relationship between stomatal parameters and the production of red chili (Capsicum annuum L) under shade treatment conditions. This research was conducted in the field with three kinds of treatments, namely (1) control (without shade), (2) 50% shade, and (3) 80% shade. The parameters observed in this study were the number of stomatal, pore stomatal, stomatal area. The data were then analyzed using the correlation coefficient (r) calculation approach. The results showed that the closest relationship was found in the stomatal area variable with a pore area of 0.98. The stomatal characteristic that has the closest relationship with the production of red chili (Capsicum annuum L) is the pore area with a value of r = 0.73. These results indicate that pore area can be used as an indicator of crop production level.

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Improving KNN Algorithm Based on Weighted Attributes by Pearson Correlation Coefficient and PSO Fine Tuning

Cited by 7 publications

References 13 publications

Contribution of vegetation restoration to carbon sequestration driven by ex‐situ poverty alleviation and relocation in ecologically fragile areas—Taking Guizhou, China, as a case

Contribution of vegetation restoration to carbon sequestration driven by ex‐situ poverty alleviation and relocation in ecologically fragile areas—Taking Guizhou, China, as a case

Deep learning based optical orbital angular momentum demultiplexing under high scattering

Correlation coefficient estimation of red chili (Capsicum annuum L) stomatal parameters under shade treatment condition

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