Economic Dispatch (ED) is an important issue in the modern power system operation. This paper proposes an improved stochastic linear cross-entropy algorithm, namely ISCE for solving the ED problem, which is a non-convex, non-linear and non-differential ...

This paper presents a study evaluating different acoustic feature map representations in two-dimensional convolutional neural networks (2D-CNN) on the speech dataset for various speech-related activities. Specifically, the task involves identifying ...

This paper provides a comparative performance analysis of both shallow and deep machine learning classifiers for speech recognition task using frame-level phoneme classification. Phoneme recognition is still a fundamental and equally crucial initial ...

Air quality has always been a hot issue of concern to the people, the environmental protection department and the government. Among the massive air quality data, abnormal data can interfere with subsequent experiments and analysis. Therefore, it is ...

With the increasing number of vehicles, traffic management has put forward higher requirements for vehicle monitoring, thus the technology of vehicle detection based on drone images has received increasing attention. Firstly, we construct a new vehicle ...

Climate change or global warming is a global threat to both human communities and natural systems. In recent years, there is an increasingly public debate on the existence of climate change or global warming, but data describing such discussions are ...

The application research of machine learning methods has attracted attention in the meteorological field. In this paper, we establish a spatiotemporal temperature deviation prediction model (PredTemp) based on convolution and long short-term memory ...

High-calorie intake can be harmful and result in numerous diseases. Standard intake of a number of calories is fundamental for keeping the right balance of calories in the human body. Currently, some techniques allow users to estimate the calorie count ...

Due to a popularization of SNS and increase of web pages, many documents can be obtained from the internet. However, it is difficult to process a huge set of document data manually. Therefore, various classification methods based on machine learning ...

Apartment rental prices are influenced by various factors. The aim of this study is to analyze the different features of an apartment and predict the rental price of it based on multiple factors. An ensemble learning based prediction model is created to ...

Path planning plays an important role in the applications of Unmanned Aerial Vehicles (UAVs). It allows the UAV to autonomously compute an optimal path from the initial point to the end by checking some specific control points or fulfill some mission ...

In recent years, the Encoder-Decoder framework has been widely used in image captioning. In the forecast period, many methods regard the input of the usage model at the previous moment as the output at the moment, which may cause the generated words to ...

EEG signal classification is a pivotal task for identification of different brain related disorders. The paper is about classification of EEG signal presenting a novel approach for the identification of whether the seizure is epileptic or normal that ...

Most scene text detection methods based on deep learning are difficult to locate texts with multi-scale shapes. The challenges of scale robust text detection lie in two aspects: 1) scene text can be diverse and usually exists in various colors, fonts, ...

The process of a classification application is usually dynamic and long. During the process of an application, better classification application effect can be acquired by enlarging and adjusting the training dataset continuously, for example, modifying ...

Aspect-level sentiment analysis is a fine-grained natural language processing task. For traditional deep learning models, they cannot accurately construct the aspect-level sentiment features. Such as, for the sentence of "the movie is very funny, but ...

The machine learning regression model is based on the assumption of normal distribution. In this paper, we mainly study the probability distribution of the machine learning model and the effect of the convergence values of different loss functions on ...

Convolutional neural networks (CNNs) are extremely important building blocks for abstract deep learning algorithm constructs regarding visual interpretation especially when it comes to synthetic aperture radar (SAR) images. An ongoing research is being ...

In this paper, we present a low-dimensional vector representation method for the concepts and instances of an ontology. The main idea is to transform the ontological entities into digestible data for machine learning and deep learning algorithms that ...

With the improvement of people's living standards, people's consumption of meat is getting higher and higher, and pork has become the core of Chinese meat production and consumption structure. Among pig farmers, retail investors account for more than ...