[PDF] Top 20 An Extreme Learning Machine Approach to Effective Energy Disaggregation
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An Extreme Learning Machine Approach to Effective Energy Disaggregation
... the energy consumption literature, the classification of the electrical loads in a house is usually divided into two groups - Intrusive Appliance Load Monitoring and Non-Intrusive Appliance Load Monitoring - ... See full document
18
Convolutional neural network extreme learning machine for effective classification of hyperspectral images
... solution, extreme learning machine (ELM) has attracted increasingly attentions in pattern recognition such as face recognition and hyperspectral image (HSI) ...in effective extraction of the ... See full document
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Local block multilayer sparse extreme learning machine for effective feature extraction and classification of hyperspectral images
... Abstract—Although Extreme Learning Machines (ELM) have been successfully applied for the classification of hyperspectral images (HSIs), they still suffer from three main ...for effective feature ... See full document
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Multi label Learning Based on Kernel Extreme Learning Machine
... improved approach is to compute the smallest norm of the output weights in ...another approach is to introduce kernel tricks into classifier ...kernel extreme learning machine to ... See full document
9
Kernelized Extreme Learning Machine with Levenberg Marquardt Learning Approach towards Intrusion Detection
... The proposed IDS is experimented using the Waikato Environment for Knowledge Analysis (WEKA) and the dataset used is KDD Cup99 dataset. WEKA is a complete set of Java class libraries that execute several state-of-the-art ... See full document
7
Rank based Pseudoinverse Computation in Extreme Learning Machine for large Datasets
... called Extreme Learning Machine (ELM) as an alternative to iterative techniques which is a three-step learning algorithm based on universal approximation theorem of ...gradient-based ... See full document
6
The Use of Machine Learning in Situational Management in Relation to the Tasks of the Power Industry
... of machine learning methods (artificial neural networks (ANN) and genetic algorithms (GA) to form management actions when applying the concept of situational management for intelligent support of strategic ... See full document
6
A graph-based signal processing approach for low-rate energy disaggregation
... available energy monitors are still in their infancy [6], ...state machine and then transit from state to state, based on user ...the learning process time-dependency in running appliances as well as ... See full document
7
Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia
... the machine learning (ML) (or statistical model) that is now being experimented in a wide variety of climate ...former approach was superior as evidenced by the lower root mean square errors, lower ... See full document
14
A New Health Assessment Prediction Approach: Multi-Scale Ensemble Extreme Learning Machine
... data-driven approach for remaining useful life prediction of aircraft ...proposed approach is an ensemble of serially connected extreme learning ...proposed approach is evaluated under ... See full document
7
Effective parallelisation for machine learning
... of learning algorithms without further mathematical derivations and without writing dedicated code, while at the same time maintaining theoretical performance ...many learning algorithms to polylogarithmic ... See full document
12
An Effective Approach for Clickbait Detection Based on Supervised Machine Learning Technique
... Yahoo research team has developed a Clickbait detection algorithm (Biyani, Tsiout- siouliklis et al. 2016). They analysed the article and the title to extract features used to detect Clickbaits. They used several text ... See full document
12
Named Entity Recognition for Telugu Language
... Abstract—Named entity recognition (NER) is a subtask of information extraction that seeks to locate and classify elements in text into predefined categories such as names of persons, locations, organizations, date, ... See full document
8
An Effective Machine Learning Approach For Disease Predictive Modelling In Medical Application
... Regression. Machine learning technique, ...the machine learning model were ...six machine learning methods and two traditional methods such as Support Vector Machine ... See full document
6
An Advanced Mechatronic Approach to Open Machine-Control Design
... mechatronic approach to machine control, which introduces an integrated and interdisciplinary method to holistic machine ...cutting machine. In addition, it applies a new approach to ... See full document
18
Cost Optimized Hybrid System in Digital Advertising using Machine Learning
... websites. Machine Learning and Artificial intelligence is now widely used to understand the current trends and to know the characteristics of people who might be interested in the contents of their ... See full document
6
An Improved Approach of Intention Discovery with Machine Learning for POMDP-based Dialogue Management
... ECAs can be used as virtual embodiments of embodied agents, which are driven more or less by artificial intelligence rather than real people. Automated online assistants are examples of avatars used in this way. Such ... See full document
156
A Machine Learning Approach to Sentence Ordering for Multidocument Summarization and Its Evaluation
... This second stage of MDS has received lesser attention compared to the first stage. Chronological ordering; ordering sentences according to the pub- lished date of the documents they belong to [6], is one solution to this ... See full document
12
Kernel-Based Multilayer Extreme Learning Machines for Representation Learning
... For transfer learning the effective representation in source tasks is transferred to the target task, so that the performance of target task can be improved. For example, in speech emotion recognition, only ... See full document
9
FORECASTING PROFITABILITY IN EQUITY TRADES USING RANDOM FOREST, SUPPORT VECTOR MACHINE AND XGBOOST
... new machine learning technique known as Extreme Gradient Boosting (Xgboost) is applied to solve multiple machine learning problems in diverse ...Boosting machine learning ... See full document
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