Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector functional link (dRVFL), general regression neural network (GRNN), multivariate adaptive regression spline (MARS), online sequential extreme learning machine (OSELM) and extreme gradient boosting decision tree (XGBoost) when compared with observed river salinity data. Also, the KELM‐BSSADE model effectively identified optimal inputs through the Boruta‐XGBoost (B‐XGB) feature selection method. Four metaheuristic‐based KELM models were developed, utilizing grey wolf optimizer, whale optimization, slime mould algorithm and equilibrium optimizer, further illustrating the capability of KELM‐BSSADE in estimating potential salinity in river water. By accurately estimating potential salinity, KELM‐BSSADE can assist in optimizing irrigation practices, ensuring that agricultural demands are met while minimizing the risk of salinity‐related crop damage.
The current research deals with practical studies that explain to the Iraqi consumer multiple instances about the phenomenon of water hammer which occur in the water pipeline operating with pressure. It concern a practical study of the characteristics of this phenomenon and economically harmful to the consumer the same time. Multiple pipe fittings are used aimed to reduce this phenomenon and its work as alternatives to the manufactured arresters that used to avoid water hammer in the sanitary installations, while the consumer did not have any knowledge as to the non-traded for many reasons, including the water pressure decreases in the networks and the use of consumer pumps to draw water directly from the network. Study found a number of
... Show MoreWell-dispersed Cu2FeSnSe4 (CFTSe) nanoparticles were first synthesized using the hot-injection method. The structure and phase purity of as-synthesized CFTSe nanoparticles were examined by X-ray diffraction (XRD) and Raman spectroscopy. Their morphological properties were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The average particle sizes of the nanoparticles were about 7-10 nm. The band gap of the as-synthesized CFTS nanoparticles was determined to be about 1.15 eV by ultraviolet-visible (UV-Vis) spectrophotometry. Photoelectrochemical characteristics of CFTSe nanoparticles were also studied, which indicated their potential application in solar energy water splitting.
Construction and operation of (2 m) parabolic solar dish for hot water application were illustrated. The heater was designed to supply hot water up to 100 oC using the clean solar thermal energy. The system includes the design and construction of solar tracking unit in order to increase system performance. Experimental test results, which obtained from clear and sunny day, refer to highly energy-conversion efficiency and promising a well-performed water heating system.
Water saturation is the most significant characteristic for reservoir characterization in order to assess oil reserves; this paper reviewed the concepts and applications of both classic and new approaches to determine water saturation. so, this work guides the reader to realize and distinguish between various strategies to obtain an appropriate water saturation value from electrical logging in both resistivity and dielectric has been studied, and the most well-known models in clean and shaly formation have been demonstrated. The Nuclear Magnetic Resonance in conventional and nonconventional reservoirs has been reviewed and understood as the major feature of this approach to estimate Water Saturation based on T2 distribution. Artific
... Show MoreThis research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there
is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated
This research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated that th
... Show MoreTime series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ
... Show MoreGroundwater is an important source of fresh water especially in countries having a decrease in or no surface water; therefore itis essential to assess the quality of groundwater and find the possibility of its use in different purposes (domestic; agricultural; animal; and other purposes). In this paper samples from 66 wells lying in different places in Baghdad city were used to determine 13 water parameters, to find the quality of groundwater and evaluate the possibility of using it for human, animal and irrigation by calculating WQI, SAR, RSC and Na% and TDS indicators. WQI results showed that the groundwater in all wells are not qualified for human use, while SAR and RSC indicated that most samples are suitable for irrigation use, and
... Show MoreIn this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.