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Counter Propagation Network Based Extreme Learning Machine
The extreme learning machine (ELM), a new learning algorithm for single hidden layer feedforward neural networks (SLFN), has drawn interest of a...
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Classification of cancer microarray data using a two-step feature selection framework with moth-flame optimization and extreme learning machine
Analysis of microarray gene expression data for the detection/classification of cancer is one of the common approaches adopted worldwide. However,...
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Streamflow prediction in mountainous region using new machine learning and data preprocessing methods: a case study
Accurate streamflow estimation is crucial for proper water management for irrigation, hydropower, drinking and industrial purposes. The main aim of...
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Performance Comparison of Different HTM-Spatial Pooler Algorithms Based on Information-Theoretic Measures
Hierarchical temporal memory (HTM) is a promising unsupervised machine-learning algorithm that models key principles of neocortical computation. One...
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Incremental Quaternion Random Neural Networks
Quaternion, as a hypercomplex number with three imaginary elements, is effective in characterizing three- and four-dimensional vector signals....
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Evolution Through Large Models
This chapter pursues the insightInsight that large language modelsLarge language models (LLMs) trained to generate code can vastly improve the...
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Employing RNN and Petri Nets to Secure Edge Computing Threats in Smart Cities
The Industrial Internet of Things (IIoT) revolution has led to the development a potential system that enhances communication among a city's assets....
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Improved Sparrow Search Algorithm with the Extreme Learning Machine and Its Application for Prediction
The prediction accuracy and generalization ability of extreme learning machine (ELM) are reduced by randomly generated weight and threshold before...
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Extreme learning machine and correntropy criterion-based hybrid precoder for 5G wireless communication systems
Application of massive multiple input multiple output (mMIMO) in millimeter wave (mmWave) band is a promising solution for 5G communication due to...
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EDense: a convolutional neural network with ELM-based dense connections
The explosive growth of geospatial data is increasing requirements for automatic and efficient data learning abilities. Many deep learning methods...
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Evolutionary Optimization of Convolutional Extreme Learning Machine for Remaining Useful Life Prediction
Remaining useful life (RUL) prediction is a key enabler for making optimal maintenance strategies. Data-driven approaches, especially employing...
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Selective ensemble of doubly weighted fuzzy extreme learning machine for tumor classification
Malignant epithelial cell tumor also known as cancer is a deadly disease requiring a very costly and complex treatment. Early and accurate diagnosis...
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An integrated model based on deep kernel extreme learning machine and variational mode decomposition for day-ahead electricity load forecasting
Accurate short-term electricity load forecasts are critical for the secure and economic operation of power systems. This paper presents a...
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Smart hydropower management: utilizing machine learning and deep learning method to enhance dam’s energy generation efficiency
Renewable energy sources and hydroelectric power generation in large parts of the electricity market are crucial as environmental pollution worsens ....
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Forecasting adversities of COVID-19 waves in India using intelligent computing
The second wave of the COVID-19 pandemic outburst triggered enormously all over India. This ill-fated and fatal brawl affected millions of Indian...
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A two-stream abnormal detection using a cascade of extreme learning machines and stacked auto encoder
Identifying anomalous activity is a heavy task, and this has led to the progression in the domain of deep learning for video surveillance. With the...
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Short-Term Wind Speed Forecasting Based on PSO-ELM
In view of the low prediction accuracy of short-term wind speed, for ELM, the connection weight and hidden layer threshold of input layer and hidden...
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Particle Swarm Optimization-Based Extreme Learning Machine for COVID-19 Detection
COVID-19 (coronavirus disease 2019) is an ongoing global pandemic caused by severe acute respiratory syndrome coronavirus 2. Recently, it has been...
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Performance of Selected Nature-Inspired Metaheuristic Algorithms Used for Extreme Learning Machine
This work presents a research on Nature Inspired Metaheuristic Algorithms (MA) used as optimizers in training process of Machine Learning method...
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Improved river water-stage forecasts by ensemble learning
Forecasting water stages is of significance to river and reservoir management. However, conventional models sometimes fail to perform accurately, as...
