Artificial neural network for chemical engineers

Instructor: Gholamreza Zahedi
Product ID: 706343
Training Level: Basic
  • 19
  • March 2020
    Thursday
  • 10:00 AM PDT | 01:00 PM EDT
    Duration: 60 Min
ANN is the one of the latest solutions that can be used in solving research and development works. The course is specially designed for researchers and engineers who need to use ANN in modelling, parameter estimation, control and optimization.

Live Online Training
March 19, Thursday 10:00 AM PDT | 01:00 PM EDT | Duration: 60 Min

$229.00
One Dial-in One Attendee
$599.00
Group-Max. 10 Attendees/Location
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Super Deal - Get CD/USB Drive Free!

recorded version

$299.00
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Recorded Link and Ref. material will be available in My CO Section 48 hrs after completion of Live training

Training CD / USB Drive

$399.00
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CD/USB and Ref. material will be shipped within 15 business days after completion of Live training

Combo Offers

Live + Recorded Version

$399.00

Live + Training CD/USB

$499.00

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Read Frequently Asked Questions

Why Should You Attend:

  • Artificial intelligence is revolutionizing industries.
  • ANN is the best techniques for predicting several out puts based on several input data.
  • Data mining and data analysis is much easier using ANN techniques.
  • With difficult modeling ANN is the fastest and the most accurate modeling technique.
  • ANN is superior than statistical regression models.
  • In lack of any knowledge and by having data, ANN will forecast system behavior.

Students and anyone who intends to understand and apply ANN solutions in industry and problem formulation should attend this course. Then course provides introduction to ANN. It starts with simple neuron model and then discusses ANN structures. Common ANN structures are discussed. MATLAB command for creating such structures also will be discussed.

Areas Covered in the Webinar:

  • Introduction
  • Neuron model and Transfer functions
  • Multiple layer of neurons
  • Perceptron learning rule
  • Training multiple perceptron
  • Working with Matlab ANN toolbox for perceptron
  • Multi layer Perceptron (MLP)
  • Pattern recognition with MLP
  • Back propagation algorithm
  • Applying Back propagation in Matlab environment
  • Data pre-post processing and generalization
  • Faster training
  • Case study 1: Hydrotreater unit in refinery
  • Case study 2: Prediction of hydrate formation temperature
  • Case study 3: Estimation of Sour Natural Gas Water Content
  • Case study 4: Self-Compacting Concrete strength prediction
  • Case study 5: Pine apple thermal degradation (forecasting)
  • Degradation (forecasting

Who Will Benefit:

  • Engineers, researchers, data analysts who are interested in learning ANN techniques.

From

  • Oil and gas, chemical industries

Free Materials:

  • Reference documents
  • Rule documents or guidance
  • Checklist
  • SOP template
  • Easy fill in forms
  • Articles
Instructor Profile:
Gholamreza Zahedi

Gholamreza Zahedi
Director of Engineering, Precision Plant Molecules

Dr Zahedi is professional engineer licensed at several states in Unites State and Chartered Engineer licensed at UK. He has over 15 years of experience both in academic and industrial sector. He has published over 100 highly cited and high impact factor journal papers, two books and several book chapters. His area of expertise are process modeling and optimization, artificial intelligence, process design and commercialization.

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Refund Policy

Registrants may cancel up to two working days prior to the course start date and will receive a letter of credit to be used towards a future course up to one year from date of issuance. ComplianceOnline would process/provide refund if the Live Webinar has been cancelled. The attendee could choose between the recorded version of the webinar or refund for any cancelled webinar. Refunds will not be given to participants who do not show up for the webinar. On-Demand Recordings can be requested in exchange.

Webinar may be cancelled due to lack of enrolment or unavoidable factors. Registrants will be notified 24hours in advance if a cancellation occurs. Substitutions can happen any time.

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