scholarly journals Hydrogeochemistry and groundwater quality appraisal of part of south Chennai coastal aquifers, Tamil Nadu, India using WQI and fuzzy logic method

2014 ◽  
Vol 4 (4) ◽  
pp. 341-350 ◽  
Author(s):  
S. Krishna Kumar ◽  
R. Bharani ◽  
N. S. Magesh ◽  
Prince S. Godson ◽  
N. Chandrasekar
Keyword(s):  
Fuzzy Logic ◽  
Groundwater Quality ◽  
Coastal Aquifers ◽  
Tamil Nadu ◽  
Quality Appraisal ◽  
Fuzzy Logic Method ◽  
Logic Method

scholarly journals Hydrochemical Analysis and Fuzzy Logic Method for Evaluation of Groundwater Quality in the North Chengdu Plain, China

2019 ◽  
Vol 16 (3) ◽  
pp. 302 ◽  
Author(s):  
Adam Mohamed ◽  
Liu Dan ◽  
Song Kai ◽  
Mohamed Mohamed ◽  
Elsiddig Aldaw ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Groundwater Quality ◽  
Evaluation Method ◽  
Quality Standard ◽  
Chengdu Plain ◽  
The North ◽  
Drinking Purposes ◽  
Fuzzy Logic Method ◽  
Logic Method

Groundwater is a major water resource in the North Chengdu Plain, China. The research objective is to determine the quality and suitability of groundwater for drinking purposes within the vicinity of a shallow, unconsolidated aquifer of Quaternary age. In this study, a detailed investigation was conducted to define the hydrochemical characteristics that control the quality of groundwater, based on traditional methods. Considering the uncertainties linked with water resources and the environmental complications, the fuzzy logic method was used in the determination of groundwater quality for more precise findings that support decision-making. To achieve such an objective, sixteen water quality guidelines were used to determine groundwater quality status in six selected wells. The results showed that the groundwater is neutral, very hard, and fresh in nature. Dominating cations and anions are in the order of Ca 2 + > Na + > Mg 2 + > K + and HCO 3 - > SO 4 2 - > Cl - . The Piper trilinear diagram demonstrates that the hydrochemical facies of groundwater are mostly of Ca-HCO 3 type. Statistical analysis denotes a positive correlation between most of the chemical parameters. The study took the results of the fuzzy logic evaluation method into consideration, to classify the samples into five groups according to the Chinese groundwater quality standard (GB/T 14848-93) for their suitability for domestic use. The results demonstrated that the quality of the groundwater samples is within grade II and III, and is suitable for drinking purposes. The comprehensive evaluation of groundwater quality is critical to aid sensitive policy decisions, and the proposed approach can guarantee reliable findings to that effect. The results of this study would also be helpful to future researches related to groundwater quality assessment.

scholarly journals Using WSR-88D Polarimetric Data to Identify Bird-Contaminated Doppler Velocities

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Yuan Jiang ◽  
Qin Xu ◽  
Pengfei Zhang ◽  
Kang Nai ◽  
Liping Liu
Keyword(s):  
Fuzzy Logic ◽  
Real Data ◽  
Radar Data ◽  
Second Step ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
Fuzzy Logic Method ◽  
Automated Technique ◽  
Migrating Birds ◽  
Logic Method

As an important part of Doppler velocity data quality control for radar data assimilation and other quantitative applications, an automated technique is developed to identify and remove contaminated velocities by birds, especially migrating birds. This technique builds upon the existing hydrometeor classification algorithm (HCA) for dual-polarimetric WSR-88D radars developed at the National Severe Storms Laboratory, and it performs two steps. In the first step, the fuzzy-logic method in the HCA is simplified and used to identify biological echoes (mainly from birds and insects). In the second step, another simple fuzzy logic method is developed to detect bird echoes among the biological echoes identified in the first step and thus remove bird-contaminated velocities. The membership functions used by the fuzzy logic method in the second step are extracted from normalized histograms of differential reflectivity and differential phase for birds and insects, respectively, while the normalized histograms are constructed by polarimetric data collected during the 2012 fall migrating season and sorted for bird and insects, respectively. The performance and effectiveness of the technique are demonstrated by real-data examples.

scholarly journals Feature Extraction in Six Blocks to Detect and Recognize English Numbers

2021 ◽  
pp. 3790-3803
Author(s):  
Heba Kh. Abbas ◽  
Haidar J. Mohamad
Keyword(s):  
Fuzzy Logic ◽  
Feature Extraction ◽  
Computational Cost ◽  
Absolute Error ◽  
Suggested Method ◽  
Support Vector ◽  
Horizontal Line ◽  
Svm Algorithm ◽  
Fuzzy Logic Method ◽  
Logic Method

    The Fuzzy Logic method was implemented to detect and recognize English numbers in this paper. The extracted features within this method make the detection easy and accurate. These features depend on the crossing point of two vertical lines with one horizontal line to be used from the Fuzzy logic method, as shown by the Matlab code in this study. The font types are Times New Roman, Arial, Calabria, Arabic, and Andalus with different font sizes of 10, 16, 22, 28, 36, 42, 50 and 72. These numbers are isolated automatically with the designed algorithm, for which the code is also presented. The number’s image is tested with the Fuzzy algorithm depending on six-block properties only. Groups of regions (High, Medium, and Low) for each number showed unique behavior to recognize any number. Normalized Absolute Error (NAE) equation was used to evaluate the error percentage for the suggested algorithm. The lowest error was 0.001% compared with the real number. The data were checked by the support vector machine (SVM) algorithm to confirm the quality and the efficiency of the suggested method, where the matching was found to be 100% between the data of the suggested method and SVM. The six properties offer a new method to build a rule-based feature extraction technique in different applications and detect any text recognition with a low computational cost.

scholarly journals Pemetaan Tingkat Kerawanan Longsor Berdasarkan Curah Hujan dan Geologi Menggunakan Metode Fuzzy Logic Di Kecamatan Leupung Kabupaten Aceh Besar

2018 ◽  
Vol 3 (2) ◽  
pp. 434-441
Author(s):  
Rasyid Alkhoir Lubis ◽  
Muhammad Rusdi ◽  
Hairul Basri
Keyword(s):  
Fuzzy Logic ◽  
Data Analysis ◽  
Analysis Data ◽  
Fuzzy Logic Method ◽  
Input Variables ◽  
Logic Method

Abstrak. Penelitian ini bertujuan untuk mengetahui tingkat kerawanan longsor di Kecamatan Leupung Kabupaten Aceh Besar. Penelitian ini dilakukan menggunakan SIG dengan Metode Fuzzy Logic. Curah Hujan dan Geologi sebagai variabel input dan tingkat kerawanan longsor sebagai variabel output metode fuzzy logic. Beberapa tahapan yang dilakukan dalam metode ini antara lain : fuzzyfication, inferensi dan defuzzyfication. Secara umum, tahapan penelitian persiapan, pra analisis data, analisis data dan output.. Penelitian ini dilakukan karena Kecamatan Leupung berbukit, berlereng, tersusun dari material sedimen termasuk batuan pegunungan dan memiliki curah hujan yang lebih tinggi dibandingkan dengan kecamatan lainnya di lingkup Kabupaten Aceh Besar.Hasil penelitian memperoleh hasil bahwa Kecamatan Leupung didominasi dengan tingkat kerawanan longsor kategori rendah dan sedang. Tingkat kerawanan longsor rendah seluas 16.486,01 ha (97,97 %) dan tingkat kerawanan longsor sedang seluas 342,37 ha (2,03 %). Kedua faktor yaitu curah hujan dan geologi saling mempengaruhi sehingga membedakan nilai defuzzyfication serta kelas kerawanan longsor. Abstract. This study aims to determine the level of landslide vulnerability in Leupung District, Aceh Besar District. This research was conducted using GIS with Fuzzy Logic Method. Rainfall and Geology as input variables and landslide vulnerability as output variables fuzzy logic method. Some of the steps performed in this method include: fuzzyfication, inference and defuzzyfication. In general, the stages of preparatory research, pre-data analysis, data analysis and output. This research was conducted because the hilly Leupung District, the slopes, composed of sedimentary materials including mountainous rocks and had higher rainfall compared to other sub-districts in Aceh Besar .The result of this research is that Leupung District is dominated by low and medium category avalanche vulnerability. Low landslide vulnerability of 16,486.01 ha (97.97%) and moderate landslide vulnerability of 342.37 ha (2.03%). Both factors are rainfall and geology influence each other so as to distinguish the defuzzyfication value and the class of landslide vulnerability.

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