In rock mechanics, the study of shear strength on the structural surface is crucial to evaluating the stability of engineering rock mass. In order to determine the shear strength, a key parameter is the joint roughness coefficient (JRC). To express and analyze JRC values, Ye et al. have proposed JRC neutrosophic numbers (JRC-NNs) and fitting functions of JRC-NNs, which are obtained by the class...

Nitrogen is an essential nutrient element in crop photosynthesis and yield improvement. Thus, it is urgent and important to accurately estimate the leaf nitrogen contents (LNC) of crops for precision nitrogen management. Based on the correlation between LNC and reflectance spectra, the hyperspectral LiDAR (HSL) system can determine three-dimensional structural parameters and biochemical changes...

Soft Computing technologies are the main topics of this book. This chapter provides the basic knowledge of fuzzy systems (FSs), neural networks (NNs), and genetic algorithms (GAs). Readers who have already studied these technologies may skip the appropriate sections. To understand the functions of FSs, NNs, and GAs, one needs to imagine a multi-dimensional input–output space or searching space....

This paper provides a short overview of neural networks (NNs) in real world industrial applications. We rst outline some of the most important features of NNs a ecting for the developing of industrial applications. We also provide lists of application areas and industrial sectors of neural networks within the Europe. Finally, some real world NN applications are reviewed, with discussion of the ...

Little research has been conducted to investigate highly advanced ESL learners’ written production of suggestions when addressing interlocutors of lower social power. The present study fills this gap by examining non-native speaking (NNS) composition instructors’ pragmatic choices of suggestions as compared to those made by their native speaking (NS) counterparts when providing written feedback...

A number of machine learning (ML) techniques have recently been proposed to solve color constancy problem in computer vision. Neural networks (NNs) and support vector regression (SVR) in particular, have been shown to outperform many traditional color constancy algorithms. However, neither neural networks nor SVR were compared to simpler regression tools in those studies. In this article, we pr...

Neural networks (NNs), such as multi layer perceptrons and radial basis function architectures, proved to be powerful tools in many problems where the objective is robust classification. However, in applications that require simultaneous segmentation and recognition, such as speech and handwriting recognition, NNs were used with much less success. In this work, we introduce an architecture for ...

Supplier selection problem (SSP) is a problem to select the best among suppliers based on input and output data of the suppliers. Since different uncontrollable and unpredictable parameters are affecting selection, choosing the best supplier is a complicated process. Data Envelopment Analysis (DEA) is a method for measuring efficiency and inefficiencies of Decision Making Units (DMUs). While, t...

This paper reports on a preliminary study on second language (L2) learners’ interlanguage pragmatic (ILP) development in academic written discourse by examining how epistemic modality is used by non-native speaker (NNS) writers compared with NS writers in both native speaker (NS) and NNS corpus data. This study also investigates how NNS writers gradually develop interlanguage pragmatic competen...

In this article we deal with a quite general topic in evolutionary structure optimization, namely redundancy in the encoding due to isomorphic structures. This problem is well known in topology optimization of neural networks (NNs). In the context of structure optimization of NNs we observe similar phenomena of rare and frequent structures as are known from molecular biology. The degree to whic...