scholarly journals Charge Plan Model for Steelmaking-Continuous Casting Section

Metals ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1196
Author(s):  
Fei Yuan ◽  
Shuangping Wu ◽  
Wei Song ◽  
Anjun Xu
Keyword(s):  
Continuous Casting ◽  
Algorithm Analysis ◽  
Mutation Operators ◽  
Casting Section ◽  
Proposed Model ◽  
Steel Grades ◽  
The Difference ◽  
A Charge ◽  
Crossover And Mutation ◽  
Charge Plan

Pursuing the intellectualization of a steelmaking plant and developing a charge plan of the steelmaking-continuous casting section are critical in metallurgy engineering. Herein, we aim to develop a charge plan model based on the operation of the steelmaking-continuous casting section to minimize the penalty values of residual materials; of a contract not selected and the penalty values that is caused by the difference in steel grades, the width and the delivery time between slabs in the same charge. We introduce an improved elitist genetic algorithm (IEGA), define the matching chromosome coding and decoding strategies, and suggest improving the selection, crossover, and mutation operators. Finally, we verify the proposed model and algorithm on the production data of a real enterprise. We clarify the applicability of developing a charge plan based on model analysis and demonstrate the effectiveness of the IEGA through algorithm analysis.

Finding Community of Brain Networks Based on Neighbor Index and DPSO with Dynamic Crossover

2020 ◽  
Vol 15 (4) ◽  
pp. 287-299
Author(s):  
Jie Zhang ◽  
Junhong Feng ◽  
Fang-Xiang Wu
Keyword(s):  
Brain Function ◽  
Brain Networks ◽  
Discrete Particle Swarm Optimization ◽  
Mri Brain ◽  
Mutation Operators ◽  
Neural Unit ◽  
Crossover And Mutation ◽  
The Brain ◽  
Index Table ◽  
Dynamic Crossover

Background: : The brain networks can provide us an effective way to analyze brain function and brain disease detection. In brain networks, there exist some import neural unit modules, which contain meaningful biological insights. Objective:: Therefore, we need to find the optimal neural unit modules effectively and efficiently. Method:: In this study, we propose a novel algorithm to find community modules of brain networks by combining Neighbor Index and Discrete Particle Swarm Optimization (DPSO) with dynamic crossover, abbreviated as NIDPSO. The differences between this study and the existing ones lie in that NIDPSO is proposed first to find community modules of brain networks, and dose not need to predefine and preestimate the number of communities in advance. Results: : We generate a neighbor index table to alleviate and eliminate ineffective searches and design a novel coding by which we can determine the community without computing the distances amongst vertices in brain networks. Furthermore, dynamic crossover and mutation operators are designed to modify NIDPSO so as to alleviate the drawback of premature convergence in DPSO. Conclusion: The numerical results performing on several resting-state functional MRI brain networks demonstrate that NIDPSO outperforms or is comparable with other competing methods in terms of modularity, coverage and conductance metrics.

TABU PROGRAMMING: A NEW PROBLEM SOLVER THROUGH ADAPTIVE MEMORY PROGRAMMING OVER TREE DATA STRUCTURES

2011 ◽  
Vol 10 (02) ◽  
pp. 373-406 ◽  
Author(s):  
ABDEL-RAHMAN HEDAR ◽  
EMAD MABROUK ◽  
MASAO FUKUSHIMA
Keyword(s):  
Search Algorithm ◽  
Benchmark Problems ◽  
Problem Solver ◽  
Learning Tools ◽  
Mutation Operators ◽  
Tree Data ◽  
Tree Data Structure ◽  
Comprehensive Framework ◽  
Rate Of Success ◽  
Crossover And Mutation

Since the first appearance of the Genetic Programming (GP) algorithm, extensive theoretical and application studies on it have been conducted. Nowadays, the GP algorithm is considered one of the most important tools in Artificial Intelligence (AI). Nevertheless, several questions have been raised about the complexity of the GP algorithm and the disruption effect of the crossover and mutation operators. In this paper, the Tabu Programming (TP) algorithm is proposed to employ the search strategy of the classical Tabu Search algorithm with the tree data structure. Moreover, the TP algorithm exploits a set of local search procedures over a tree space in order to mitigate the drawbacks of the crossover and mutation operators. Extensive numerical experiments are performed to study the performance of the proposed algorithm for a set of benchmark problems. The results of those experiments show that the TP algorithm compares favorably to recent versions of the GP algorithm in terms of computational efforts and the rate of success. Finally, we present a comprehensive framework called Meta-Heuristics Programming (MHP) as general machine learning tools.

Modeling and simulation of saturated double rotor induction machine

2018 ◽  
Vol 37 (3) ◽  
pp. 1139-1165
Author(s):  
Koosha Choobdari Omran ◽  
Ali Mosallanejad
Keyword(s):  
Temperature Effects ◽  
Power Efficiency ◽  
Reactive Power ◽  
Induction Machine ◽  
Transient Behavior ◽  
State Equations ◽  
Content Type ◽  
Proposed Model ◽  
The Difference ◽  
Park Transformation

Purpose Double rotor induction machine (DRIM) is a particular type of induction machine (IM) that has been introduced to improve the parameters of the conventional IM. The purpose of this study is to propose a dynamic model of the DRIM under saturated and unsaturated conditions by using the equations obtained in this paper. Also, skin and temperature effects are considered in this model. Design/methodology/approach First, the DRIM structure and its performance will be briefly reviewed. Then, to realize the DRIM model, the mathematical equations of the electrical and mechanical part of the DRIM will be presented by state equations in the q-d axis by using the Park transformation. In this paper, the magnetizing fluxes saturation is included in the DRIM model by considering the difference between the amplitudes of the unsaturated and saturated magnetizing fluxes. The skin and temperature effects are also considered in this model by correcting the rotor and stator resistances values during operation. Findings To evaluate the effects of the saturation and skin effects on DRIM performance and validate the model, the machine is simulated with/without consideration of saturation and skin effects by the proposed model. Then, the results, including torque, speed, stator and rotor currents, active and reactive power, efficiency, power factor and torque-speed characteristic, are compared. In addition, the performance of the DRIM has been investigated at different speed conditions and load variations. The proposed model is developed in Matlab/Simulink for the sake of validation. Originality/value This paper presents an understandable model of DRIM with and without saturation, which can be used to analyze the steady-state and transient behavior of the motor in different situations.

scholarly journals Investigating the Temporal Effect of User Preferences with Application in Movie Recommendation

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Wen-Jun Li ◽  
Qiang Dong ◽  
Yan Fu
Keyword(s):  
Rapid Development ◽  
User Preferences ◽  
Mobile Internet ◽  
Smart Devices ◽  
Data Sets ◽  
Rating Data ◽  
Temporal Effect ◽  
Proposed Model ◽  
Target User ◽  
The Difference

As the rapid development of mobile Internet and smart devices, more and more online content providers begin to collect the preferences of their customers through various apps on mobile devices. These preferences could be largely reflected by the ratings on the online items with explicit scores. Both of positive and negative ratings are helpful for recommender systems to provide relevant items to a target user. Based on the empirical analysis of three real-world movie-rating data sets, we observe that users’ rating criterions change over time, and past positive and negative ratings have different influences on users’ future preferences. Given this, we propose a recommendation model on a session-based temporal graph, considering the difference of long- and short-term preferences, and the different temporal effect of positive and negative ratings. The extensive experiment results validate the significant accuracy improvement of our proposed model compared with the state-of-the-art methods.

Diagnosis of infertility from adenomyosis and endometriosis through entroxon based intelligent water drop back propagation neural networks

2022 ◽  
pp. 1-9
Author(s):  
P. Vijayalakshmi ◽  
K. Muthumanickam ◽  
G. Karthik ◽  
S. Sakthivel
Keyword(s):  
Clustering Algorithm ◽  
Water Drop ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Uterine Wall ◽  
Health Issues ◽  
Testing Dataset ◽  
Proposed Model ◽  
Fuzzy C Means Clustering ◽  
The Difference

Adenomyosis is an abnormality in the uterine wall of women that adversely affects their normal life style. If not treated properly, it may lead to severe health issues. The symptoms of adenomyosis are identified from MRI images. It is a gynaecological disease that may lead to infertility. The presence of red dots in the uterus is the major symptom of adenomyosis. The difference in the extent of these red dots extracted from MRI images shows how significant the deviation from normality is. Thus, we proposed an entroxon-based bio-inspired intelligent water drop back-propagation neural network (BIWDNN) model to discover the probability of infertility being caused by adenomyosis and endometriosis. First, vital features from the images are extracted and segmented, and then they are classified using the fuzzy C-means clustering algorithm. The extracted features are then attributed and compared with a normal person’s extracted attributes. The proposed BIWDNN model is evaluated using training and testing datasets and the predictions are estimated using the testing dataset. The proposed model produces an improved diagnostic precision rate on infertility.

scholarly journals A Novel Active Contours Model for Environmental Change Detection from Multitemporal Synthetic Aperture Radar Images

2020 ◽  
Vol 12 (11) ◽  
pp. 1746
Author(s):  
Salman Ahmadi ◽  
Saeid Homayouni
Keyword(s):  
Synthetic Aperture Radar ◽  
Change Detection ◽  
Active Contours ◽  
Training Data ◽  
Synthetic Aperture ◽  
Data Sets ◽  
Difference Image ◽  
Proposed Model ◽  
The Difference ◽  
Aperture Radar

In this paper, we propose a novel approach based on the active contours model for change detection from synthetic aperture radar (SAR) images. In order to increase the accuracy of the proposed approach, a new operator was introduced to generate a difference image from the before and after change images. Then, a new model of active contours was developed for accurately detecting changed regions from the difference image. The proposed model extracts the changed areas as a target feature from the difference image based on training data from changed and unchanged regions. In this research, we used the Otsu histogram thresholding method to produce the training data automatically. In addition, the training data were updated in the process of minimizing the energy function of the model. To evaluate the accuracy of the model, we applied the proposed method to three benchmark SAR data sets. The proposed model obtains 84.65%, 87.07%, and 96.26% of the Kappa coefficient for Yellow River Estuary, Bern, and Ottawa sample data sets, respectively. These results demonstrated the effectiveness of the proposed approach compared to other methods. Another advantage of the proposed model is its high speed in comparison to the conventional methods.

ACCURATE ANALYSIS OF GLOBAL INTERCONNECTS IN NANO-FPGAs

NANO ◽  
2009 ◽  
Vol 04 (03) ◽  
pp. 171-176 ◽  
Author(s):  
DAVOOD FATHI ◽  
BEHJAT FOROUZANDEH
Keyword(s):  
Propagation Delay ◽  
Modeling Method ◽  
Accurate Analysis ◽  
Proposed Model ◽  
Simulation Results ◽  
The Difference ◽  
A New Technique ◽  
Global Interconnects ◽  
Technology Nodes ◽  
Model Technique

This paper introduces a new technique for analyzing the behavior of global interconnects in FPGAs, for nanoscale technologies. Using this new enhanced modeling method, new enhanced accurate expressions for calculating the propagation delay of global interconnects in nano-FPGAs have been derived. In order to verify the proposed model, we have performed the delay simulations in 45 nm, 65 nm, 90 nm, and 130 nm technology nodes, with our modeling method and the conventional Pi-model technique. Then, the results obtained from these two methods have been compared with HSPICE simulation results. The obtained results show a better match in the propagation delay computations for global interconnects between our proposed model and HSPICE simulations, with respect to the conventional techniques such as Pi-model. According to the obtained results, the difference between our model and HSPICE simulations in the mentioned technology nodes is (0.29–22.92)%, whereas this difference is (11.13–38.29)% for another model.

Simulation of the Pressure-Bearing Capacity Test Model in Architectural Decoration Design

2014 ◽  
Vol 716-717 ◽  
pp. 391-394
Author(s):  
Li Mei Guo ◽  
Ai Min Xiao
Keyword(s):  
Genetic Algorithm ◽  
Bearing Capacity ◽  
Test Method ◽  
Test Model ◽  
Improved Genetic Algorithm ◽  
Good Convergence ◽  
Mutation Operators ◽  
Process Pressure ◽  
Calculation Process ◽  
Crossover And Mutation

in architectural decoration process, pressure-bearing capacity test is the foundation of design, and is very important. To this end, a pressure-bearing capacity test method in architectural decoration design is proposed based on improved genetic algorithm. The selection, crossover and mutation operators in genetic algorithm are improved respectively. Using its fast convergence characteristics eliminate the pressure movement in the calculation process. The abnormal area of pressure-bearing existed in buildings which can ensure to be tested is added, to obtain accurate distribution information of the abnormal area of pressure-bearing. Simulation results show that the improved genetic algorithm has good convergence, can accurately test the pressure-bearing capacity in architectural decoration.

scholarly journals Light Leakage of Multidomain Vertical Alignment LCDs Using a Colorimetric Model in the Dark State

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
Chuen-Lin Tien ◽  
Rong-Ji Lin ◽  
Shang-Min Yeh
Keyword(s):  
Liquid Crystal ◽  
Contrast Ratio ◽  
Liquid Crystal Displays ◽  
Vertical Alignment ◽  
Dark State ◽  
Proposed Model ◽  
Color Shift ◽  
Depolarization Of Light ◽  
The Difference ◽  
Color Filters

Light leakage from liquid crystal displays in the dark state is relatively larger and leads to a degraded contrast ratio and color shift. This work describes a novel colorimetric model based on the Muller matrix that includes depolarization of light propagating through liquid crystal molecules, polarizers, and color filters. In this proposed model, the chromaticity can be estimated in the bump and no-bump regions of an LCD. We indicate that the difference between simulation and measurement of chromaticity is about 0.01. Light leakage in the bump region is three times that in no-bump region in the dark state.

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