Comparison of LLR,MLP, Elman,NNARX and ANFIS Models—with a case study in solar radiation estimation

Despite the widespread application of nonlinear mathematical models, comparative studies of different models are still a huge task for modellers. This is because a large number of trial and error processes are needed to develop each model, so the workload will be multiplied into an unmanageable level if many types of models are involved. This study presents an efficient approach by using the Gamma test (GT) to select the input variables and the training data length, so that the trial and error workload can be greatly reduced. The methodology is tested in estimating solar radiation at the Brue catchment, UK. Several nonlinear models have been developed efficiently with the aid of the GT, including local linear regression, multi-layer perceptron (MLP), Elman neural network, neural network auto-regressive model with exogenous inputs (NNARX) and adaptive neuro-fuzzy inference system (ANFIS). This work is only feasible within the time and resources constraint, due to the GT in reducing huge workload of the trial and error process.     

Evaluation of Tailings from a Porphyry Copper Mine based on Joint Simulation of Contaminants

Natural Resources Research - Tailings from porphyry copper mines contain environmentally harmful amounts of elements such as copper, molybdenum, lead and cobalt. Geostatistical simulation of...     

Interaction of groundwater with Lake Urmia in Iran

Being a large hyper‐saline water body, Lake Urmia in north‐western Iran deals with a gradual decline in its water level. Most of the studies on Lake Urmia have neglected the groundwater issue. In this study, as a direct approach, the interaction between the groundwater level and the lake water level is investigated both in time and space by analysing the groundwater data compiled from observation wells surrounding the lake. Baseflow separation is considered as an indirect approach to understand the groundwater contribution to the river network flowing into the lake. It is determined that about 70% of run‐off in the rivers draining into the lake is born in the form of baseflow. An interaction between the lake and the groundwater storage is clearly seen from the analysis to conclude that groundwater has a potential to recharge the lake. Thus, the shrinkage of water level in Lake Urmia could be expected to accelerate with the drastic use of groundwater, which will be a disaster with no return.     

Application of the Dynamic Cone Penetrometer (DCP) for determination of the engineering parameters of sandy soils

Determination of the in situ engineering properties of foundation materials has always been a challenge for geotechnical engineers and, thus, several methods have been developed so far. Dynamic Cone Penetration (DCP) test is one of the most versatile amongst them. In the present research, a light weight simple DCP device was developed and used for evaluation of the engineering properties of sandy soils in laboratory conditions. The device consisted of an 8-kg hammer that drops over a height of 575 mm, and drives a 60° cone tip with 20 mm base diameter into the ground. To control the validation of the results, laboratory direct shear and plate load tests were used as reference tests. The soil sample was a poorly graded sandy soil (SP) taken from alluvial deposits of the Tehran plain. All DCP tests and PLTs were undertaken on compacted soil in a mould with 700 mm diameter and 700 mm height. Based on the results of the experiments, the relationships between Dynamic Penetration Index (DPI), relative density (D_r), modulus of elasticity (E), shear modulus (G), modulus of subgrade reaction (K_S), and the friction angle of the soil were obtained with a high coefficient of determination (> 90%). The repeatability of the test results was also evaluated by calculating the coefficient of variations (C_v), which was less than 30% for all tests.     

Using value engineering to optimize flood forecasting and flood warning systems: Golestan and Golabdare watersheds in Iran as case studies

Flood occurrence has always been one of the most important natural phenomena, which is often associated with disaster. Consequently, flood forecasting (FF) and flood warning (FW) systems, as the most efficient non-structural measures in reducing flood loss and damage, are of prime importance. These systems are low cost and the time required for their implementation is relatively short. It is emphasized that for designing the components of these systems for various rivers, climatic conditions and geographical settings different methods are required. One of the major difficulties during implementing these systems in different projects is the fact that sometimes the main functions of these systems are ignored. Based on a systematic and practical approach and considering the components of these systems, it would be possible to extract the most essential key functions of the system and save time, effort and money by this way. For instance, in a small watershed with low concentration and small lead time, the main emphasis should be on predicting and monitoring weather conditions. In this article, different components of flood forecasting and flood warning systems have been introduced. Then analysis of the FF and FW system functions has been undertaken based on the value engineering (VE) technique. Utilizing a functional view based on function analysis system technique (FAST), the total trend of FF and FW functions has been identified. The systematic trend and holistic view of this technique have been used in optimizing FF and FW systems of the Golestan province and Golabdare watersheds in Iran as the case studies.     

A Geometric Computational Model for Calculation of Longwall Face Effect on Gate Roadways

In this paper a geometric computational model (GCM) has been developed for calculating the effect of longwall face on the extension of excavation-damaged zone (EDZ) above the gate roadways (main and tail gates), considering the advance longwall mining method. In this model, the stability of gate roadways are investigated based on loading effects due to EDZ and caving zone (CZ) above the longwall face, which can extend the EDZ size. The structure of GCM depends on four important factors: (1) geomechanical properties of hanging wall, (2) dip and thickness of coal seam, (3) CZ characteristics, and (4) pillar width. The investigations demonstrated that the extension of EDZ is a function of pillar width. Considering the effect of pillar width, new mathematical relationships were presented to calculate the face influence coefficient and characteristics of extended EDZ. Furthermore, taking GCM into account, a computational algorithm for stability analysis of gate roadways was suggested. Validation was carried out through instrumentation and monitoring results of a longwall face at Parvade-2 coal mine in Tabas, Iran, demonstrating good agreement between the new model and measured results. Finally, a sensitivity analysis was carried out on the effect of pillar width, bearing capacity of support system and coal seam dip.     

Long-term trends of seasonal dusty day characteristics—West Iran

In order to examine the seasonal characteristics of the dust events over western parts of Iran, surface observations from 27 meteorological stations for the period 1951–2014 were analyzed to obtain spatial distributions and temporal variations and trend of dusty day frequency (DDF). Trends of DDF were analyzed by Mann–Kendall and Sen’s estimator of slope nonparametric statistics. Three meteorological stations were selected in north (Tabriz), middle (Kermanshah), and south of the study area (Ahwaz) as reference stations for detecting the regional differences of DDFs. The results showed that DDF is a variable season by season but in general, DDF increases from north to south and from east to west of Iran. The maximum of DDF is monitored in May, June, and July. There are tangible seasonal increasing–decreasing periods in which these changes are logically related with seasonal changes. Regardless of the existence of the maximum DDF in south and southwest of study area, the most intensive increasing DDF trend is calculated in west middle areas. The most widespread and intensive increasing DDF pattern in west of Iran is observed when it is spring. In this case, the dust storms replaced the rainfalls. Distance from dust sources, major movement ways of dust transporting synoptic systems, regional effective wind activity (such as Shamal wind), and arrangement of high mountains are the known factors affecting frequency variation, distribution, and rate of the trend of all the dust phenomena in west of Iran.