propagation techniques
Propagation Techniques Of Pyracantha Crenulata (D. Don.) M. Roem
... Pyracantha crenulata M.Roem, syn. Crataegus crenulata Roxb. of Rosaceae family (locally known as Ghingharu) is an evergreen shrub which attains height up to 5 m and found in Kumaun Himalayas between 2000 ft to 7000 ft in ...
5
Propagation techniques in probabilistic expert systems
... variables in the waste incinerator problem given Lauritzen's evidence148 3.11 Graphs of the marginal distributions of the simulated continuous.. variables in the waste i[r] ...
338
A Review of Propagation Techniques and Isothiocyanates Content in Wasabi (Wasabia japonica Matsum.)
... Wasabi propagation especially with the use of in vitro culture and the possible influence of the content of ITCs‑allyl isothiocyanate (AITC) on important substances in ...
6
Detection of Heart Diseases using Machine Learning and Data Mining
... back propagation techniques ...classification techniques that detected the patient’s risk level by classifying it using data mining classification techniques such as Probabilistic ...
7
Performance Study on Rule-based Classification Techniques across Multiple Database Relations
... classification techniques namely Decision tree, PART, RIPPER and RIDOR based on tuple-id propagation techniques [23], [24], ...tuple-id propagation technique based on the following criteria: ...
7
Thinking inside the Box: Tissue Culture for Plant Propagation in a Key Ecological Species, Andropogon gerardii
... species, propagation techniques might be the only option for working with ge- notypes or ecotypes of ...Greenhouse propagation can take months to several years [20] [75]-[81], even with added growth ...
17
Design Approach for a Novel and Efficient Wireless Underground Communication System by using Electromagnetic Waves
... signal propagation techniques by using EM waves encounter three major problems in the soil medium: high path loss, dynamic channel condition and large antenna ...signal propagation technique for ...
9
Sound propagation and force chains in granular materials
... Linearity and nonlinearity. The photoelastic parti- cles allow us to directly visualize an important particle- scale nonlinearity present in the system. Due to the non-zero Poisson ratio of the polymer material ( ν ≈ 0 . ...
6
Vol 9, No 4 (2019)
... Artificial neural networks are a kind of artificial intelligence that works in the principle of a human brain. It is comprises of highly interconnected processing elements called neurons which process the given ...
13
Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
... The response of laser machin ing phenomenon has been modeled using Artificia l Neura l Net work (ANN) to predict surface roughness. The best out of eight evaluated mu ltilayer back-propagation neural network model ...
6
Optimized Face Recognition Technique based on PCA and RBF Neural Network
... the techniques PCA with neural network using Back Propagation algorithm and the proposed approach PCA using optimized RBF neural network with gradient descent activation ...two techniques for AT ...
6
Multiple satellite observations of oceanic planetary waves: techniques and findings
... TOPEX/Poseidon (T/P) and ERS-1 and -2 allowed a convincing demonstration of the ubiquity of planetary waves at mid-latitudes in the oceans (Chelton and Schlax, 1996), and the study of their propagation ...
10
Mass Production Techniques of Arbuscular Mycorrhizal Fungi: Major Advantages and Disadvantages: A Review
... Numerous techniques have been developed in the past few decades for the mass production of arbuscular mycorrhizal (AM) ...production techniques of AM fungi is the obligate nature of this biotrophic fungus ...
6
Modeling batch annealing process using data mining techniques for cold rolled steel sheets
... mining techniques. The main advantages of modelling with data mining techniques are: high speed in data processing, acceptable accuracy in obtained results and simplicity in using of this ...mining ...
6
Implementation of Neural Network Back Propagation Training Algorithm on FPGA
... The Back propagation training algorithm code for 4:4:2:2:4 neural network with PURELIN transfer function is implemented in MATLAB. The neural network is trained for image compression and decompression using back ...
7
Passive ranging of near field targets in the audio frequency band
... Declaration Certificate Acknowledgement Abstract Table of Contents Chapter One Thesis Overview 1.0 Introduction Chapter Two Introduction and Techniques 2.0 Introduction 2.1 Propagation o[r] ...
165
Australian Journal of Basic and Applied Sciences
... Ghorbani et al. (2016) had built three models to predict water flow using real datasets from three various stations in Iran. It is taken as a comparison study for the monthly forecasting of flow. They used SVM, radial ...
15
Review Techniques of Data Privacy in Cloud Using Back Propagation Neural Network
... In this collaborative learning the participating parties carry out learning not only on their own data sets, also on others’ data sets. With the recent new computing Environment such as Cloud Computing, In order to ...
5
Identifying hand gestures using sEMG for human machine interaction
... extraction techniques are used as function extracted and cascade forward back propagation neural network (CFBPNN), pattern recognizance network are utilized to gestures ...
9
Hybrid Techniques for Arabic Letter Recognition
... extraction techniques: Yule-Walker spectrum feature, Walsh spectrum feature and Mel Frequency Cepstral ...Back Propagation Neural Network (FFBPNN) is ...
8