N. Zabet Pishkhani; S.M. Seyedian; A. Heshmat Pour; H. Rouhani
Abstract
Introduction: In recent years, according to the intelligent models increased as new techniques and tools in hydrological processes such as precipitation forecasting. ANFIS model has good ability in train, construction and classification, and also has the advantage that allows the extraction of fuzzy ...
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Introduction: In recent years, according to the intelligent models increased as new techniques and tools in hydrological processes such as precipitation forecasting. ANFIS model has good ability in train, construction and classification, and also has the advantage that allows the extraction of fuzzy rules from numerical information or knowledge. Another intelligent technique in recent years has been used in various areas is support vector machine (SVM). In this paper the ability of artificial intelligence methods including support vector machine (SVM) and adaptive neuro fuzzy inference system (ANFIS) were analyzed in monthly precipitation prediction.
Materials and Methods: The study area was the city of Gonbad in Golestan Province. The city has a temperate climate in the southern highlands and southern plains, mountains and temperate humid, semi-arid and semi-arid in the north of Gorganroud river. In total, the city's climate is temperate and humid. In the present study, monthly precipitation was modeled in Gonbad using ANFIS and SVM and two different database structures were designed. The first structure: input layer consisted of mean temperature, relative humidity, pressure and wind speed at Gonbad station. The second structure: According to Pearson coefficient, the monthly precipitation data were used from four stations: Arazkoose, Bahalke, Tamar and Aqqala which had a higher correlation with Gonbad station precipitation. In this study precipitation data was used from 1995 to 2012. 80% data were used for model training and the remaining 20% of data for validation. SVM was developed from support vector machines in the 1990s by Vapnik. SVM has been widely recognized as a powerful tool to deal with function fitting problems. An Adaptive Neuro-Fuzzy Inference System (ANFIS) refers, in general, to an adaptive network which performs the function of a fuzzy inference system. The most commonly used fuzzy system in ANFIS architectures is the Sugeno model since it is less computationally exhaustive and more transparent than other models. A consequent membership function (MF) of the Sugeno model could be any arbitrary parameterized function of the crisp inputs, most like lya polynomial. Zero and first order polynomials were used as consequent MF in constant and linear Sugeno models, respectively. In addition, the defuzzification process in Sugeno fuzzy models is a simple weighted average calculation. The fuzzy space was divided via grid partitioning according to the number of antecedent MF, and each fuzzy region was covered with a fuzzy rule.
Results Discussion: The statistical results showed that in first structure determination coefficient values for both the training and test was not good performance in precipitation prediction so that ANFIS and SVM had determination coefficient of 0.67 and 0.33 in training phase and 0.45 and 0.40 in test phase. Also the error RMSE values showed that both models had failed to predict precipitation in first structure. The results of second structure in precipitation prediction showed that determination coefficient of ANFIS at training and testing was 0.93 and 0.87 respectively and RMSE was 7.06 and 9.28 respectively. MBE values showed that the ANFIS underestimated at training phase and overestimated at test phase. Determination coefficient of SVM at training and testing was 0.89 and 0.91 respectively and RMSE was 9.28 and 5.59 respectively. SVM underestimated precipitation at train phase and overestimated it at test phase. ANFIS and SVM modeled precipitation using precipitation gauging stations with reasonable accuracy. Determining coefficient in the test phase was almost the same for ANFIS and SVM but the RMSE error of SVM model was about 20% lower than the ANFIS. The coefficient of determination and error values indicated SVM had greater accuracy than ANFIS. ANFIS overestimated precipitation for less than 20 mm but for higher values of uniformly distributed around the 1:1. SVM underestimated precipitation for more than 90 mm precipitation due to the low number of data in the training phase, which made this model, did not train well. When meteorological parameters were introduced as input, minimum determination coefficient and maximum error in the test phase occurred while humidity parameters were removed. By removing any of the parameters of temperature, pressure and wind speed the error values and coefficient of determination in test phase was approximately equal.
Conclusion: The potential of the support vector machine (SVM) and neuoro fuzzy inference system (ANFIS) in monthly precipitation pattern were analyzed. In order to model, two data sets were used containing meteorological parameters (temperature, humidity, pressure and wind speed) and the stations precipitation. The results showed that the simulated precipitation using meteorological parameters by ANFIS and SVM had low accuracy. Precipitation forecasting using stations precipitation in the region had good accuracy by ANFIS and SVM. Comparing the results of this study showed the high efficiency of SVM in simulating precipitation. This method can be successfully used in modeling precipitation to increase efficiency of precipitation modelling.
hojjat ghorbani vaghei; Hosseinali Bahrami; R. Mazhari; A. Heshmatpour
Abstract
Introduction: Maintaining soil moisture content at about field capacity and reducing water loss in near root zone plays a key role for developing soil and water management programs. Clay pot or porous pipe is a traditional sub-irrigation method and is ideal for many farms in the world’s dry land with ...
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Introduction: Maintaining soil moisture content at about field capacity and reducing water loss in near root zone plays a key role for developing soil and water management programs. Clay pot or porous pipe is a traditional sub-irrigation method and is ideal for many farms in the world’s dry land with small and medium sized farms and gardens and is still used limitedly in dry lands of India, Iran, Pakistan, the Middle East, and Latin-America. Clay capsule is one of porous pipes in sub irrigation that is able to release water in near root zone with self- regulative capacity. Watering occurs only in amounts that the plants actually need (this amount is equal to field capacity) and released water in near root zone without electricity or use of an automatic dispenser.
Materials and Methods: A study was carried out in 2013 on the experimental field of agriculture faculty of Tarbiat Modares University, to study the effect of two irrigation types on qualitative and quantitative characters in grape production (Vitis vinifera L.). In order to provide the water requirement of grape plant were used porous clay capsules for sub irrigation with height and diameter of 12 cm and 3.5 cm and dripper with Neta film type for drip irrigation, respectively. Porous clay capsules provided from soil science group at Tarbiat Modares University. In this research, the volume of water delivered to grape plants during entire growth period in two different irrigation methods was measured separately with water-meters installed at all laterals. The water consumption, yield production and water use efficiency were evaluated and compared in two drip and porous clay irrigation systems at veraison phonological stages. In the veraison stages, cluster weight, cluster length, solid solution and pH content were measured in grape fruits. Leaf chlorophyll content and leaf water content were also measured in two irrigation systems.
Results and Discussion: The results of fruit quality characteristics showed that cluster weight, cluster length, solid solution and pH content has not significant different at 5% level in two system irrigation. Also, the foliar analysis showed that chlorophyll content and relative humidity of leaf has not been affected in two irrigation systems. Meanwhile, irrigation types were significantly effect on water consumption and water use efficiency. The average water consumption and yield production with buried clay capsules and drip irrigation methods on grapevine plant were 4050 and 6668 M3.ha-1 and 14.2 and 14.8 Ton.ha-1 respectively. The reducing water consumption with buried clay capsules irrigation method in related to drip irrigation was 39% on grapevine plants. Meanwhile, the average yield production with buried clay capsules and drip irrigation methods on grapevine plant was 14.2 and 14.8 Ton.ha-1 respectively. Also, the statistics analysis show that the yield and component yield have not significant different at 5% level in the surface and subsurface irrigation. According to the water consumption and yield production, using buried porous clay capsules created a better water use efficiency than drip irrigation method. In other words, Iran has been localized at arid and semi arid and have huge water consumption in agriculture, and therefore it is necessary to optimize water consumption especially in agriculture using new technology. According to the results of this research, using buried porous clay capsules is recommended in order to optimize water consumption for grape plants in different place in arid and semi-arid regions of Iran.
Conclusion: The purpose of an efficient irrigation system is to apply the water in such a way that the largest fraction thereof is available for beneficial use by the plant. According to the experimental results reported here, it could be concluded that the reducing water consumption with buried clay capsules irrigation method in related to drip irrigation was 39% on grapevine plants. Meanwhile, the average yield production with buried clay capsules and drip irrigation methods on grapevine plant was 14.2 and 14.8 Ton.ha-1 respectively. Also, the statistics analysis show that the yield and component yield have not significant different at 5% level in the surface and subsurface irrigation. The final result, it could be concluded that the porous clay capsules have a good ability to providing water requirement of grape plant. The grape irrigation in huge area of Iran is doing with a traditional method and the authors of this work believe that porous clay capsules have a high water saving potential and good capability for irrigation of various types of crops.
Keywords: Grape plant, Porous pipe, Soil moisture, Water use efficiency, Yield
