Feature Extraction of Tomato Growth Model using Greenhouse Monitoring System

2019 ◽  
Author(s):  
Luthfi Aminulloh ◽  
Wahjoe Tjatur Sesulihatien ◽  
Dadet Pramadihanto
Keyword(s):  
Feature Extraction ◽  
Monitoring System ◽  
Growth Model ◽  
Tomato Growth

Feature Extraction for Non-intrusive Load Monitoring System

2021 ◽  
Author(s):  
Qiuzhan Zhou ◽  
Jiahui Wei ◽  
Mingyu Sun ◽  
Cong Wang ◽  
Jing Rong ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Monitoring System ◽  
Load Monitoring

AUTOMATIC FROG CALLS MONITORING SYSTEM: A MACHINE LEARNING APPROACH

2001 ◽  
Vol 01 (02) ◽  
pp. 165-186 ◽  
Author(s):  
GARY G. YEN ◽  
QIANG FU
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Environmental Monitoring ◽  
Monitoring System ◽  
Wavelet Packet ◽  
Digital Signal ◽  
Automatic Monitoring ◽  
Individual Identification ◽  
Biological Research ◽  
Automatic Monitoring System

Automatic recognition of frog vocalization is considered a valuable tool for a variety of biological research and environmental monitoring applications. In this research an automatic monitoring system, which can recognize the vocalizations of four species of frogs and can identify different individuals within the species of interest, is proposed. For the desired monitoring system, species identification is performed first with the proposed filtering and grouping algorithm. Individual identification, which can estimate frog population within the specific species, is performed in the second stage. Digital signal pre-processing, feature extraction, dimensionality reduction, and neural network pattern classification are performed step by step in this stage. Wavelet Packet feature extraction together with two different dimension reduction algorithms are synergistically integrated to produce final feature vectors, which are to be fed into a neural network classifier. The simulation results show the promising future of deploying an array of continuous, on-line environmental monitoring systems based upon nonintrusive analysis of animal calls.

REDUCED STATE–VARIABLE TOMATO GROWTH MODEL

1999 ◽  
Vol 42 (1) ◽  
pp. 255-265 ◽  
Author(s):  
J. W. Jones ◽  
A. Kenig ◽  
C. E. Vallejos
Keyword(s):  
Growth Model ◽  
State Variable ◽  
Tomato Growth ◽  
Reduced State

scholarly journals Destruction Feature Extraction of Prefabricated Residential Building Components Based on BIM

2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Peili Zhao ◽  
Xiaohong Liu ◽  
Zhisheng Liang
Keyword(s):  
Feature Extraction ◽  
Monitoring System ◽  
Residential Building ◽  
Building Construction ◽  
Superposition Method ◽  
Strength Theory ◽  
Space Truss ◽  
Angle Space ◽  
Building Components ◽  
Damage Characteristic

In order to improve the damage feature extraction effect of prefabricated residential building components and improve the structural stability of prefabricated residential components, this paper applies BIM technology to the structural feature analysis of prefabricated residential components. Moreover, this paper adopts the simple superposition method and combines the first strength theory of material mechanics to derive the formula for calculating the cracking torque of prefabricated residential building components under compound torsion. In addition, based on the variable-angle space truss model, this paper uses a simple superposition method to derive the calculation formula for the ultimate torque of composite torsion of fabricated residential building components and applies it to the BIM fabricated residential model. Finally, this paper constructs an intelligent BIM prefabricated residential building construction damage characteristic monitoring system. Through experimental research, it can be seen that the intelligent BIM prefabricated residential building construction damage feature monitoring system proposed in this paper can monitor the damage characteristics of prefabricated residential building construction and can predict the evolution of subsequent building features.

Development, calibration and validation of a greenhouse tomato growth model: II. Field calibration and validation

1993 ◽  
Vol 43 (2) ◽  
pp. 165-183 ◽  
Author(s):  
E. Dayan ◽  
H. van Keulen ◽  
J.W. Jones ◽  
I. Zipori ◽  
D. Shmuel ◽  
...  
Keyword(s):  
Growth Model ◽  
Calibration And Validation ◽  
Field Calibration ◽  
Greenhouse Tomato ◽  
Tomato Growth
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