# A Practical Group Symbol and Group Name Approach (PSNA) according to EN ISO 14688-2:2018
## 1 Introduction  
Soil classification systems are very crucial to the description and identification of soils. The utilization of the same soil classification principles among engineers all over the world can help efforts to understand, define, and interpret material and results. A soil classification system aims to facilitate communication between different groups of engineers. Engineers use soil classification surveys to determine the potential behavior and limitations of soil. At present, the soil classification systems of different countries vary significantly according to sieve sets, the diameter sizes of particles, and their percentage of total mass. A series of soil classification systems have been proposed across the world on the basis of grain size distribution. The first classification system based on soil texture was proposed by [PERSON] [1; 2]. [PERSON] [3] developed a classification and identification system based on grain size distribution called the Airfield classification system for soils in the early 1940s. The Unified Soil Classification System is one of the most widely used systems in the world and is in accordance with the US standard ASTM D2487 [4]. The AASHTO (American Association of State Highway and Transportation Officials) classification system [5] is well-known in road works. Soil classification systems are based on the standards of the respective countries. As such, in India, there is the Indian Standard [6]; in Australia, there is the Australian Standard [7]; in the United Kingdom, there is the British Standard [8]; in China, there is the Chinese Standard [9]; in Japan, there is the Japanese Standard [10]; and in Germany, there is DIN [11], to name only a few. These standards are used in geotechnical investigations. Some have since been withdrawn, while some have had some changes to improve the description of the material. Recently, there have been some studies using different methods to classify the soils. [PERSON] et al. [12] developed a soil classification system for describing water and chemical transport in South Carolina. The system was based on surface texture, clay mineralogy, and the nature of the soil structure. Numerous field experiments were carried out to test the classification system. [PERSON] [13] tried to provide a quantitative soil classification based on plasticity index, liquid limit, and clay content using a neural network. The results show that neural networks can be used for the prediction of soil classification. [PERSON] et al. [14] assessed the similarities and differences between sand soils according to their grain size distribution using different classification systems. [PERSON] and [PERSON] [15] proposed a soil classification system based on EN ISO 14688-1:2002 [16] and EN ISO 14688-2:2004 [17]. A different marking system was applied with this classification system according to these standards. In this method, the symbolization starts with a secondary fraction and with small letters. [PERSON] and [PERSON] [18] proposed a revised soil classification system for engineering applications. The study included data-based gravimetric and volumetric analyses to anticipate fines and sand fraction thresholds. The study focused on the physical properties of soil mixtures. [PERSON] et al. [19] proposed a soil classification system in 2014 and they developed it because of the novelties of identification and description in EN ISO 14688-1:2018 [20] and EN ISO 14688-2:2018 [21]. [PERSON] et al. [22] compared six different classification systems for fine-grained soils. After reviewing these classification systems, a chronological order was obtained. [PERSON] et al. [23] focused on a new model for the prediction of soil classification. To generate these models, tests were performed on 440 specimens in order to determine the type of soil. Clay content, moisture content, specific gravity, void ratio, plastic, and liquid limit were used for the construction of the model. An algorithm called AdaBoost was employed to classify the soil.