least squares support vector machine - Globe Thesis

Keyword [least squares support vector machine] Result: 101 - 120 \| Page: 6 of 7
101.	Application Of Least Squares Support Vector Machine Regression In Scoring Wine Quality
102.	Research On Demand Forecast Of Molybdenum Mineral Logistics In China Based On Improved LSSVM
103.	Research On Techniques Of Ball-mill Vibration Signal Feature Extraction And Mill Load Parameters Online Detection
104.	Rapid Detection Of Quality Index Of Camellia Seed Oil By Infrared Spectroscopy
105.	Research On Intelligent Control System For Raw Material Preparation Of Electric Porcelain
106.	Research On Rice Quality Detection Based On Terahertz Time Domain Spectroscopy
107.	Study On Detecting Wheat Pesticide Residues Based On SERS Technology
108.	Soft Sensing And Feed Predictive Control Of Marine Lysozyme Fermentation Process Based On IFA-MLSSVM
109.	Research On Potato Crops Mechanical Damage Detection Based On Manifold Learning
110.	Research On Nondestructive Detection Of Sweet Potato Flour Using Spectral Information
111.	Optimization Of Acoustic Emission Signal Pocessing And Recognition Technology Of Fiber Tensile Fracture
112.	Research On The Control Strategy Of The Active-passive Combined Heave Compensation Device For The Tianmo Model
113.	Study On Intelligent Decision And Control Of Suspension Density Setting In Heavy Medium Separation Process With Variable Coal Quality
114.	Fault Diagnosis And Prediction System Of Mine Hoist Driven By Multi-monitoring Information
115.	Grinding Particle Size Soft Mearsurement And Loop Optimization Control
116.	Accurate Camber Detection And Intelligent Optimization Based On Machine Vision
117.	Recognition And Function Module Development Of Hob Wear State Based On Vibration Characteristic Analysis
118.	Surface Topography Characteristics And Influencing Factors Analysis And Prediction Of Ball-end Milling Hardened Steel
119.	Data-Driven Robust LS-SVR Modeling And Nonlinear Predictive Control Of Blast Furnace Ironmaking Process
120.	Research On Dynamic Monitoring Method Of Rare Earth Element Content Based On Time Series Characteristics
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