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Articles 1 - 8 of 8
Full-Text Articles in Engineering
Energy Efficiency Data Mining And Scheduling Optimization Of Discrete Workshop, Yugu Lin, Wang Yan
Energy Efficiency Data Mining And Scheduling Optimization Of Discrete Workshop, Yugu Lin, Wang Yan
Journal of System Simulation
Abstract: This paper addresses the optimization of energy consumption in discrete workshops and establishes the energy efficiency optimization model of discrete workshops. The relationship between data mining and knowledge discovery is established. Through scheduling data preprocessing and C4.5 decision tree learning algorithm, the discovery of scheduling knowledge is realized. Energy efficiency optimization calculation is achieved in discrete workshops by the combination of scheduling knowledge and improved differential evolution algorithm (IDE). By comparing with TLBO, GA and PSO, the feasibility of IDE algorithm is verified.
Feature Space Modeling For Accurate And Efficient Learning From Non-Stationary Data, Ayesha Akter
Feature Space Modeling For Accurate And Efficient Learning From Non-Stationary Data, Ayesha Akter
Doctoral Dissertations
A non-stationary dataset is one whose statistical properties such as the mean, variance, correlation, probability distribution, etc. change over a specific interval of time. On the contrary, a stationary dataset is one whose statistical properties remain constant over time. Apart from the volatile statistical properties, non-stationary data poses other challenges such as time and memory management due to the limitation of computational resources mostly caused by the recent advancements in data collection technologies which generate a variety of data at an alarming pace and volume. Additionally, when the collected data is complex, managing data complexity, emerging from its dimensionality and …
Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead
Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead
Engineering Faculty Articles and Research
Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing ASD, exploring its genetic underpinnings, and designing effective interventions. This paper provides a comprehensive review of 45 papers utilizing supervised machine learning in ASD, including algorithms for classification and text analysis. The goal of the paper is to identify and describe supervised machine learning trends in ASD literature as …
Design And Implementation Of Information Management Platform For Big Data Of Uranium, Zhou Xiaoxi, Deng Fan, Wan Lin, Yang Jun
Design And Implementation Of Information Management Platform For Big Data Of Uranium, Zhou Xiaoxi, Deng Fan, Wan Lin, Yang Jun
Coal Geology & Exploration
In order to integrate the borehole data and geological survey data of sandstone-type uranium deposits, the unified management of the borehole database was implemented, and the efficiency of integrated application of the geological data of borehole data was improved. A comprehensive information management platform for uranium was designed and implemented. For big data platform, the four-layer framework composed of the base installation, information resources, application service, user interaction was proposed. Techniques such as virtualization of cloud computing, distributive storage and parallel computing were adopted to set up the basic environment of the big data of uranium and improve the unified …
Optimization Of Material Release For Printed Circuit Board Template Based On Data Mining, Shengping Lü, Qiangsheng Yue, Liu Tao
Optimization Of Material Release For Printed Circuit Board Template Based On Data Mining, Shengping Lü, Qiangsheng Yue, Liu Tao
Journal of System Simulation
Abstract: Data mining were employed for the optimization of material release of PCB (Printed Circuit Board) template. PCB scrap ratio related parameters were specified and prediction model variables were chosen according to hypothesis test. Multiple linear regression (MLR), Chi-squared automatic interaction detector, artificial neural network and support vector machine approaches for the prediction of scrap ratio were employed. Evaluation indictors called as superfluous ratio, supplement release ratio and weighted sum of the two were presented; the material release simulation was conducted and then the four approaches were compared and MLR was taken as the preferred one. Adjust coefficient …
Mining And Validation Of Attacking Behavior In The Robocup 2d Simulation, Chen Bing, Zhang Heng, Zekai Cheng, Dong Peng, Lin Chao
Mining And Validation Of Attacking Behavior In The Robocup 2d Simulation, Chen Bing, Zhang Heng, Zekai Cheng, Dong Peng, Lin Chao
Journal of System Simulation
Abstract: Robocup is an international academic competition which focuses on artificial intelligence and robotics. The 2D simulation is one of the earliest and most influential projects in Robocup. Attacking is the core behaviour of the simulated football game, as well as the attack recognition is considered as an important part in team-confrontations. This paper selects some active and contribution index of attacking, extracts lots of attacking behaviour data of the key agents, proposes two kinds of attacking patterns of 2D simulation, as ‘separate attack’ and ‘cooperative attack’, according to the human-player actions. The following simulation tests give the accuracy of …
Data Analysis Through Social Media According To The Classified Crime, Serkan Savaş, Nuretti̇n Topaloğlu
Data Analysis Through Social Media According To The Classified Crime, Serkan Savaş, Nuretti̇n Topaloğlu
Turkish Journal of Electrical Engineering and Computer Sciences
The amount and variety of data generated through social media sites has increased along with the widespread use of social media sites. In addition, the data production rate has increased in the same way. The inclusion of personal information within these data makes it important to process the data and reach meaningful information within it. This process can be called intelligence and this meaningful information may be for commercial, academic, or security purposes. An example application is developed in this study for intelligence on Twitter. Crimes in Turkey are classified according to Turkish Statistical Institute criminal data and keywords are …
Heart Attack Mortality Prediction: An Application Of Machine Learning Methods, Issam Salman
Heart Attack Mortality Prediction: An Application Of Machine Learning Methods, Issam Salman
Turkish Journal of Electrical Engineering and Computer Sciences
The heart is an important organ in the human body, and acute myocardial infarction (AMI) is the leading cause of death in most countries. Researchers are doing a lot of data analysis work to assist doctors in predicting the heart problem. An analysis of the data related to different health problems and its functions can help in predicting the wellness of this organ with a degree of certainty. Our research reported in this paper consists of two main parts. In the first part of the paper, we compare different predictive models of hospital mortality for patients with AMI. All results …