Search
Search Results
-
A multiobjective prediction model with incremental learning ability by develo** a multi-source filter neural network for the electrolytic aluminium process
Improving current efficiency and reducing energy consumption are two important technical goals of the electrolytic aluminum process (EAP). However,...
-
Incremental learning model based on an improved CKS-PFNN for aluminium electrolysis manufacturing
Filtering neural networks (FNNs) are popular computing frameworks for process system modeling. However, they are vulnerable to non-Gaussian noise and...
-
Soft computing techniques for modelling and multi-objective optimization of magnetic field assisted powder mixed EDM process
The present work emphasizes on artificial neural network (ANN) and genetic algorithm (GA) for modelling and optimization of Magnetic Field Assisted...
-
Label propagation dictionary learning based process monitoring method for industrial process with between-mode similarity
With the development of the industrial cyber-physical systems, a small amount of labeled data and a large amount of unlabeled data are collected from...
-
Industrial consumers’ electricity market participation options: a case study of an industrial cooling process in Denmark
In a deregulated market context, industrial consumers often have multiple market participation options available to bid their flexible consumption in...
-
Robotic Flow Shop Scheduling with Parallel Machines and No-Wait Constraints in an Aluminium Anodising Plant with the CMAES Algorithm
This paper proposes a covariance matrix adaptation evolution strategy (CMAES) based algorithm for a robotic flow shop scheduling problem with...
-
Fault Diagnosis in Aluminium Electrolysis Using a Joint Method Based on Kernel Principal Component Analysis and Support Vector Machines
As a key part of aluminium smelting, the operational conditions of aluminium electrolytic cells are of great significance for the stability of the...
-
Multi-objective Optimization for Ladle Tracking of Aluminium Tap** Based on NSGA-II
In order to realize the optimization of ladle tracking of aluminium tap**, a mathematical model, which takes the grade of aluminium, the energy...
-
Estimation of Aluminium Fluoride Concentration in Aluminium Reduction Cells through a Soft Sensors Approach
This work exploits a model for Aluminium Fluoride Concentration Measurement in the Aluminium Smelting process. This process variable is usually...
-
Design and Implementation of Electrolyzer Simulation System
In this paper, we present one method to develop and design an inexpensive electrolyzer simulation system, which can be applied to the management of...
-
Soft Sensor for Fluoridated Alumina Inference in Gas Treatment Centers
The Gas Treatment Center performs a key role in the aluminum smelting process, since it strongly influences the chemical and thermal stability of the...
-
Fernziele der Nanoelektronik
Während der vergangenen vierzig Jahre folgte die Entwicklung der Mikroelektronik dem Moore#x2019;schen Gesetz, einem empirischen Gesetz, welches...
-
Study on Anode Effect Prediction of Aluminium Reduction Applying Wavelet Packet Transform
Electrolytic cell is typically nonlinear and complex system with high temperature and strong electromagnetic fields. It is also highly erosive and...
-
Strategic Evaluation of Research and Development into Embedded Energy Storage in Wind Power Generation
Embedded Energy Storage (EES) is an innovative idea presented in a previous paper. EES is associated with some major configurations of wind power...
-
Cost Estimation and Conceptual Process Planning
Engineering cost estimation is now compulsory from the very first stages of design. The later a cost issue will be detected, the more it will cost....
-
What do we know about innovation in nanotechnology? Some propositions about an emerging field between hype and path-dependency
This contribution formulates a number of propositions about the emergence of novel nanoscience and nanotechnology (N&N). Seeking to complement recent...
-
Multi-sensor recognition of electronic components
The Dempster-Shafer theory and the convex Bayesian theory have recently been proposed as alternatives to the (strict) Bayesian theory in the field...
-
Productivity Improvements through Prediction of Electrolyte Temperature in Aluminium Reduction Cell Using BP Neural Network
Primary aluminium is produced using a highly dynamic and unstable technique known as the Hall-Heroult process. An important consideration for...
-
Identifying Significant Parameters for Hall-Heroult Process Using General Regression Neural Networks
While there are many models of the neural networks that are suitable for a particular application, each model will yield different accuracy when...
-
Model-Based Control for Industrial Processes Using a Virtual Laboratory
In the metallurgical industries, thermophysical processes are used in large numbers for the processing of materials in successive stages. Those...