Standardized Variable Distances: A distance-based machine learning method

Elen, Abdullah; Avuçlu, Emre

doi:10.1016/j.asoc.2020.106855

Cited by 27 publications

(8 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, standardization can also speed up the gradient descent to find optimal solutions. In this study, Z-score standardization was used for the data processing, which can be mathematically expressed as [35]:…”

Section: Vehicle Dynamics Data Acquisitionmentioning

confidence: 99%

An Improved Deep Neural Network Model of Intelligent Vehicle Dynamics via Linear Decreasing Weight Particle Swarm and Invasive Weed Optimization Algorithms

Nie

Min

Pan

et al. 2022

Sensors

View full text Add to dashboard Cite

We propose an improved DNN modeling method based on two optimization algorithms, namely the linear decreasing weight particle swarm optimization (LDWPSO) algorithm and invasive weed optimization (IWO) algorithm, for predicting vehicle’s longitudinal-lateral responses. The proposed improved method can restrain the solutions of weight matrices and bias matrices from falling into a local optimum while training the DNN model. First, dynamic simulations for a vehicle are performed based on an efficient semirecursive multibody model for real-time data acquisition. Next, the vehicle data are processed and used to train and test the improved DNN model. The vehicle responses, which are obtained from the LDWPSO-DNN and IWO-DNN models, are compared with the DNN and multibody results. The comparative results show that the LDWPSO-DNN and IWO-DNN models predict accurate longitudinal-lateral responses in real-time without falling into a local optimum. The improved DNN model based on optimization algorithms can be employed for real-time simulation and preview control in intelligent vehicles.

show abstract

Section: Vehicle Dynamics Data Acquisitionmentioning

confidence: 99%

An Improved Deep Neural Network Model of Intelligent Vehicle Dynamics via Linear Decreasing Weight Particle Swarm and Invasive Weed Optimization Algorithms

Nie

Min

Pan

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Additionally when the features of the dataset is having different measurements it is important to centralize the complete data around mean 0 and standard deviation 1. This removes bias and all values will provide equal contribution during study [38]. To standardize the complete dataset is subjected to transform using the following equation:…”

Section: Kernel Principal Component Analysis (Kpca)mentioning

confidence: 99%

Multi Core DNN based IDS for Botnet Attacks using KPCA Reduction Techniques

Sharmila

Nagapadma

2021

Preprint

View full text Add to dashboard Cite

Research on network security has recently acquired attention in the field of the Internet of Things. In the context of security, most of the IoT devices with the internet are connected directly which results in the exploitation of private data. Nowadays, the fraudster will release novel attacks very frequently especially for IoT devices. As a result, the traditional sophisticated Intrusion Detection System (IDS) model is not suitable for the identification of vulnerabilities in IoT devices. In our research work, we propose MCDNN for IDS. MCDNN is Multi Core DNN with having parallel optimizer. Rather than a traditional dataset, this paper experiment is conducted on the BoTIoT dataset. Since IoT devices generate a huge volume of data, this work focuses on reducing huge datasets using Kernel Principal Component Analysis(KPCA) reduction technique with optimizer parallelly. To decrease false alarm rate and maintaining less computational power multi-core is introduced in our research work. This helps identification of vulnerabilities in IoT devices using deep learning techniques faster. Experimental results indicate that designing MCDNN based IDS with different optimizers parallelly achieved higher performance than those of other techniques.

show abstract

“…Machine learning algorithms can quickly process large-scale data, have high computational efficiency and excellent model effects. They have been widely used in various fields to solve real-life and academic problems [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Body Shape Recognition and Prototype Construction Based on LightGBM Algorithm

Wang

Wang²,

Liu

2022

Advances in Transdisciplinary Engineering

View full text Add to dashboard Cite

The regional characteristics of middle-aged women in Xinjiang are obvious, and the phenomenon of incompatible clothing is prominent. In order to avoid the information loss of principal component analysis or factor analysis during body type classification, this study uses the LightGBM algorithm to establish a body type recognition model based on the results of K-Means clustering, and compares it with random forest and linear regression recognition models. It is found that the LightGBM model has the best body type recognition effect. it is good. Through correlation analysis and regression analysis, regression equations between variables are obtained. Based on the new cultural prototype, Liu Ruipu women’s clothing prototype, and Donghua prototype, a clothing prototype suitable for middle-aged women in Xinjiang is established. Through virtual fitting evaluation and actual fitting, the experimental prototypes established based on the Donghua prototype and the Liu Ruipu prototype can meet the needs of middle-aged women for the comfort and aesthetics of clothing. The experimental prototype established by the Donghua prototype has the best effect.

show abstract

Standardized Variable Distances: A distance-based machine learning method

Cited by 27 publications

References 16 publications

An Improved Deep Neural Network Model of Intelligent Vehicle Dynamics via Linear Decreasing Weight Particle Swarm and Invasive Weed Optimization Algorithms

An Improved Deep Neural Network Model of Intelligent Vehicle Dynamics via Linear Decreasing Weight Particle Swarm and Invasive Weed Optimization Algorithms

Multi Core DNN based IDS for Botnet Attacks using KPCA Reduction Techniques

Body Shape Recognition and Prototype Construction Based on LightGBM Algorithm

Contact Info

Product

Resources

About

Standardized Variable Distances: A distance-based machine learning method

Cited by 27 publications

References 16 publications

An Improved Deep Neural Network Model of Intelligent Vehicle Dynamics via Linear Decreasing Weight Particle Swarm and Invasive Weed Optimization Algorithms

An Improved Deep Neural Network Model of Intelligent Vehicle Dynamics via Linear Decreasing Weight Particle Swarm and Invasive Weed Optimization Algorithms

Multi Core DN​N based IDS for Botnet Attacks using KPCA Reduction Techniques

Body Shape Recognition and Prototype Construction Based on LightGBM Algorithm

Contact Info

Product

Resources

About

Multi Core DNN based IDS for Botnet Attacks using KPCA Reduction Techniques