scholarly journals Classification of blast furnace internal state based on FLS and its application in furnace temperature prediction

2021 ◽  
Vol 252 ◽  
pp. 02041
Author(s):  
Wang Gao-peng ◽  
Zhai Hai-peng ◽  
Yan Zhen-yu ◽  
Zheng Rui-ji
Keyword(s):  
Blast Furnace ◽  
Silicon Content ◽  
Internal State ◽  
Estimation Method ◽  
Test Sample ◽  
Least Square ◽  
Training Data ◽  
State Variable ◽  
Selection Of

The real-time and accurate prediction of the molten iron silicon content of the blast furnace plays an important role in regulating the temperature of the blast furnace and stabilizing the furnace condition. When the time is large, the accuracy and credibility of the forecast results decrease rapidly, which is not conducive to on-site operators to carry out production operations according to the forecast results. To this end, this paper adds a state variable to each piece of data through the flexible least square parameter estimation method, and selects the training set in a state similar to the test sample. This makes the selection of training data more accurate and reliable. Application examples show that the method proposed in this paper improves the accuracy of silicon content prediction results and has good guiding significance for actual production operations.

Classification of silicon content variation trend based on fusion of multilevel features in blast furnace ironmaking

2020 ◽  
Vol 521 ◽  
pp. 32-45 ◽  
Author(s):  
Ke Jiang ◽  
Zhaohui Jiang ◽  
Yongfang Xie ◽  
Zhipeng Chen ◽  
Dong Pan ◽  
...  
Keyword(s):  
Blast Furnace ◽  
Silicon Content ◽  
Variation Trend ◽  
Content Variation ◽  
Blast Furnace Ironmaking

scholarly journals Hubungan Faktor Kolestrol Terhadap Gula Darah Diabetes dengan Spline Kubik Terbobot

2020 ◽  
Vol 1 (1) ◽  
pp. 32
Author(s):  
Zhazha Alifkhamulki Ramdhani ◽  
Anna Islamiyati ◽  
Raupong Raupong
Keyword(s):  
Diabetes Mellitus ◽  
Blood Sugar ◽  
Blood Sugar Level ◽  
Cross Validation ◽  
Estimation Method ◽  
Cubic Spline ◽  
Least Square ◽  
Spline Models ◽  
Sugar Levels ◽  
Selection Of

Diabetes Mellitus (DM) is often recognized through an increase in a person's blood sugar level. Factors that can affect the increase in blood sugar levels of DM patients one of which is cholesterol. It usually contains the bookkeeping of several types of cholesterol, including LDL and total cholesterol. DM data are assumed to experience heterokedasticity so that in this study analyzed using regression of weighted cubic spline nonparametric. The estimation method used is weighted least square (WLS). This study aims to obtain a weighted cubic spline model on cholesterol based DM data. The selection of the best model can be seen based on the criteria for the value of generalized cross validation (GCV) minimum. Based on the analysis obtained weighted cubic spline models for cholesterol factors for blood sugar as follows:

scholarly journals Prospectivity Mapping of Mineral Deposits in Northern Norway Using Radial Basis Function Neural Networks

Minerals ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 131 ◽  
Author(s):  
Cyril Juliani ◽  
Steinar Ellefmo
Keyword(s):  
Radial Basis Function ◽  
Basis Function ◽  
Input Data ◽  
Mean Squared Error ◽  
Training Data ◽  
Northern Norway ◽  
Radial Basis ◽  
Host Rocks ◽  
Selection Of

In this paper, the radial basis function neural network (RBFNN) is used to generate a prospectivity map for undiscovered copper-rich (Cu) deposits in the Finnmark region, northern Norway. To generate the input data for RBFNN, geological and geophysical data, including up to 86 known mineral occurrences hosted in mafic host-rocks, were combined at different resolutions. Mineral occurrences were integrated into “deposit” and “non-deposit” training sets. Running RBFNN on different input vectors, with a k-fold cross-validation method, showed that increasing the number of iterations and radial basis functions resulted in: (1) a reduction of training mean squared error (MSE) down to 0.1, depending on the grid resolution, and (2) reaching correct classification rates of 0.9 and 0.6 for training and validation, respectively. The latter depends on: (1) the selection of “non-deposit” training data throughout the study area, (2) the scale at which data was acquired, and (3) the dissimilarity of input vectors. The “deposit” input data were correctly identified by the trained model (up to 83%) after proceeding to classification of non-training data. Up to 885 km2 of the Finnmark region studied is favorable for Cu mineralization based on the resulting mineral prospectivity map. The prospectivity map can be used as a reconnaissance guide for future detailed ground surveys.

Prediction Modeling of Hot Metal Silicon Content in Blast Furnace Based on PSO-LSSVM

2013 ◽  
Vol 721 ◽  
pp. 461-465 ◽  
Author(s):  
Long Hui Wang ◽  
Song Gao ◽  
Xing Qu ◽  
Yao Geng Tang
Keyword(s):  
Blast Furnace ◽  
Silicon Content ◽  
Thermal State ◽  
Steel Tube ◽  
Least Square ◽  
Support Vector ◽  
Neural Network Modeling ◽  
Model Parameters ◽  
Stable Operation ◽  
Hot Metal

The hot metal silicon content is important for the quality of the iron, but also as an indicator of the thermal state of the furnace. In order to stable operation of the blast furnace, a model is needed to predict hot metal silicon content more accurately. Towards this goal, a model based on least square support vector machine (LSSVM) is developed to model and predict hot metal silicon content, particle swarm optimization (PSO) is adopted to search the optimal set of the LSSVM model parameters. Prediction experiment is conducted based on the data obtained from a blast furnace past operation records in a steel tube plant and being preprocessed in several different ways. The experimental results show that the proposed methods yielded more accurate predictions than the neural network modeling methods.

Use of photodynamic therapy for photodamage skin (review of literature)

2019 ◽  
Vol 1 (7) ◽  
pp. 19-23
Author(s):  
S. I. Surkichin ◽  
N. V. Gryazeva ◽  
L. S. Kholupova ◽  
N. V. Bochkova
Keyword(s):  
Photodynamic Therapy ◽  
Comparative Evaluation ◽  
Clinical Manifestations ◽  
Light Sources ◽  
Review Of Literature ◽  
Photosensitizing Agents ◽  
Selection Of

The article provides an overview of the use of photodynamic therapy for photodamage of the skin. The causes, pathogenesis and clinical manifestations of skin photodamage are considered. The definition, principle of action of photodynamic therapy, including the sources of light used, the classification of photosensitizers and their main characteristics are given. Analyzed studies that show the effectiveness and comparative evaluation in the selection of various light sources and photosensitizing agents for photodynamic therapy in patients with clinical manifestations of photodamage.

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