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Application Research of Multi-label Learning Under Concept Drift
In order to address the interference of concept drift on the results of multi-label learning algorithms, a hybrid kernel extreme learning machine is...
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Skin Cancer Detection from Dermatoscopic Images Using Hybrid Fuzzy Ensemble Learning Model
Malignant tissue in the skin is highly harmful. As melanoma is of identical look and lacks color variation, detection of skin cancer from...
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State of the Art of Ensemble Learning Approach for Crop Prediction
Agriculture has a captious part in maintaining a large population. It plays a decisive role to forward our country’s economic development. Crop...
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Extreme Learning Machine Based Identification of Malicious Users for Secure Cooperative Spectrum Sensing in Cognitive Radio Networks
Cognitive radio (CR) technology has evolved over the traditional radio to successfully utilize the unused frequency spectrum. In CR the secondary...
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Breast Cancer Prediction Using Greedy Optimization and Enlarge C4.5
Detecting Breast Cancer in the early step is significant to minimize the death rate by enhancing the available treatments. As there exists no...
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Estimation of Intact Rock Uniaxial Compressive Strength Using Advanced Machine Learning
The present investigation introduces an optimal computational model by comparing gene expression programming (GEP), least square support vector...
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Intelligent Ensemble-Based Road Crack Detection: A Holistic View
Cracks on road surfaces undermine infrastructure load-bearing capacity and endanger both motorists and pedestrians. Prompt and effective...
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HE-ELM Technique Based Transformer Protection
Various unwanted phenomena that are taken place in the transformer may occasionally mal-operate selected fault classification based protective...
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Evaluation of Concrete Characteristics Using Smart Machine Learning Techniques—A Review
Concrete is one of the most commonly used materials for a wide range of construction across the world. The heterogeneity of concrete results in wide...
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NIFTY-50 Index Forecasting Using CEEMDAN Decomposition and Deep Learning Models
This paper presents a hybrid model composed of the Complete Ensemble Empirical Mode Decomposition Adaptive Noise (CEEMDAN) technique and Convolution...
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Harnessing Nature-Inspired Soft Computing for Reinforced Soil Bearing Capacity Prediction: A Neuro-nomograph Approach for Efficient Design
The bearing capacity of soil in general is considered a key parameter in the field of geotechnical engineering, requiring field investigations and...
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Ensemble deep learning for high-precision classification of 90 rice seed varieties from hyperspectral images
To develop rice varieties with better nutritional qualities, it is important to classify rice seeds accurately. Hyperspectral imaging can be used to...
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Liver Cancer Classification Using Single Pass Neural Networks Based on Ultrasound Images: A Review
Liver cancer is amongst the most cancer-related life threats worldwide. If not detected early, most liver diseases can lead to liver cancer. Early...
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An Extensive Survey on Machine Learning-Enabled Automated Human Action Recognition Models
In recent times, human action recognition (HAR) is the most significant one because of its applications in numerous domains like entertainment,...
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Big Data—Supply Chain Management Framework for Forecasting: Data Preprocessing and Machine Learning Techniques
This article systematically identifies and comparatively analyzes state-of-the-art supply chain (SC) forecasting strategies and technologies within a...
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Voting-Based Extreme Learning Machine Approach for the Analysis of Sensor Data in Healthcare Analytics
There has been a huge surge in the production of sensor-based clinical devices for health monitoring systems over the last few years. This sudden...
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Cov-CONNET: A Deep CNN Model for COVID-19 Detection
COVID-19 emerged as a pandemic after originating in Wuhan, China, in the year 2019. As COVID-19 has affected millions of people around the globe,...
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ANFIS and Kernel Extreme Learning Machine to the Assessment and Identification of Seismic b-value as Precursor
It is important to know how to predict earthquakes, especially if you want to find patterns of earthquakes that happen often. The b-value is one of...
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Semi-supervised fuzzy-rough extreme learning machine for classification of cancer from microRNA
The miRNA is a tiny, single-stranded RNA of nearly 22 nucleotides long that is transcribed from DNA and controls the genes in protein synthesis...
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Machine and Deep Learning Algorithms for ADHD Detection: A Review
Attention Deficit Hyperactivity Disorder (ADHD) is a neuro-developmental disorder common in childhood. In 2017, a report from the WHO (World Health...