Optimized fuzzy rules illustration. by Yanyan Dong (1304145)

“…The prediction process uses a large volume of information to identify the details of resources and operational performance in industrial applications. …”

FuzzyMath excellence analysis. by Yanyan Dong (1304145)

“…The prediction process uses a large volume of information to identify the details of resources and operational performance in industrial applications. …”

Summary of related studies. by Yanyan Dong (1304145)

“…The prediction process uses a large volume of information to identify the details of resources and operational performance in industrial applications. …”

Defuzzification Output related to . by Yanyan Dong (1304145)

“…The prediction process uses a large volume of information to identify the details of resources and operational performance in industrial applications. …”

Contribution of aggregated rules in . by Yanyan Dong (1304145)

“…The prediction process uses a large volume of information to identify the details of resources and operational performance in industrial applications. …”

Relationship analysis between . by Yanyan Dong (1304145)

“…The prediction process uses a large volume of information to identify the details of resources and operational performance in industrial applications. …”

List of generated rules. by Yanyan Dong (1304145)

“…The prediction process uses a large volume of information to identify the details of resources and operational performance in industrial applications. …”

Image 1_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 3_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 10_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 4_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 8_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 2_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 9_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 6_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 7_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 5_MS4A7 based metabolic gene signature as a prognostic predictor in lung adenocarcinoma.jpeg by Yan Jiang (12139)

“…</p>Methods<p>A prognostic signature for LUAD was developed using the LASSO-Cox regression algorithm with RNA-seq data from 500 LUAD patients in The Cancer Genome Atlas database. …”

Image 7_Segmentation of tobacco shred point cloud and 3-D measurement based on improved PointNet++ network with DTC algorithm.png by Yihang Wang (4731429)

“…This model combines the weighted cross-entropy loss function to enhance the classification effect, the cosine annealing algorithm to optimize the training process, and the improved k-nearest neighbors multi-scale grouping method to enhance the model’s ability to segment the point cloud with complex morphology. …”

Image 2_Segmentation of tobacco shred point cloud and 3-D measurement based on improved PointNet++ network with DTC algorithm.png by Yihang Wang (4731429)

“…This model combines the weighted cross-entropy loss function to enhance the classification effect, the cosine annealing algorithm to optimize the training process, and the improved k-nearest neighbors multi-scale grouping method to enhance the model’s ability to segment the point cloud with complex morphology. …”

Table 1_Segmentation of tobacco shred point cloud and 3-D measurement based on improved PointNet++ network with DTC algorithm.docx by Yihang Wang (4731429)

“…This model combines the weighted cross-entropy loss function to enhance the classification effect, the cosine annealing algorithm to optimize the training process, and the improved k-nearest neighbors multi-scale grouping method to enhance the model’s ability to segment the point cloud with complex morphology. …”