One of the most important aspects of the evaluation of any aquatic system is the simulation of water quality parameters. Recently, artificial intelligence methods have been broadly applied to simulate hydrological processes. This study evaluates the potential of applying the neuro‐fuzzy system and neural network to simulate total dissolved solid and electrical conductivity levels, by employing the values of other existing water quality parameters. Consideration of these results will be important for implementing and adopting a water quality prediction model which is able to provide a useful tool for the management of water resources. In this study, water quality data were analyzed from five sampling stations over six years from 2008 to 2013, in the Langat Basin, Malaysia. An assessment of the model's performance was carried out through the correlation coefficient and mean squared error obtained from the model computation and measurement values of the dependent variables. Consequently, a close agreement between these values and their respective measured values in the quality of the groundwater were found. Accordingly, artificial intelligence approaches and adaptive neuro‐fuzzy inference system models in particular are capable of interpreting the behavior of water quality parameters.
Individually applying intelligent calculating tools, such as artificial neural network and fuzzy logic techniques, to a variety of problems is confirmed to be efficient. Recently, a growing interest in a combination of these methods has resulted in the neuro-fuzzy calculating technique. The application of the artificial neural network (ANN) and the adaptive neuro-fuzzy inference system (ANFIS) to groundwater level simulation, over 7 years from 2007 to 2013, in the Langat Basin, Malaysia, is presented in this paper. Moreover, to the time series of groundwater levels, the time series of the five most effective parameters of groundwater level, that is rainfall, humidity, evaporation, minimum temperature and maximum temperature, were applied to obtain the best input parameters for the models. The performances of the different models were studied through evaluating the related values of the mean squared error and correlation coefficient to identify an optimal model that can simulate the decreasing trend of the groundwater level and provide passable simulation. In the model, excellent performance in different statistical indices was shown. Finally, a relatively good agreement between the calculated values and their corresponding measured values for the groundwater level were found. Evaluating the results of the various kinds of models, it has been shown that the obtained results of the ANFIS model are superior to those obtained from ANNs.
For senior high school students, learning concepts in physics is increasingly more difficult when the topic is abstract and cannot be seen with the unaided eye. The research here utilized augmented reality technology and instructional design following the ADDIE model (analysis, design, development, implementation and evaluation) to develop learning media for physics, specifically the kinetic theory of gases. Preliminary analysis was conducted in a senior high school to evaluate the challenges students face when learning physics. The design of the media was based on addressing problems that the students were having. Augmented reality technology was then utilized and the implementation aimed to incorporate the physics concepts into the product. The media was evaluated by six experts. Finally, the learning media presented real-time 3D animation of gas kinetic theory with three basic competencies relevant to the topic. In the final validation, the results indicated that the developed learning media had a validity value of 3.55 out of four-point scale and good quality outcomes. As such, the developed media regarding the kinetic theory of gases is valid and effective for the process of learning and teaching. It is ready to be tested and used in actual learning environments.
Groundwater suitability for agriculture in an island with limited recharge area may easily be intluenced by seawater intrusion. The aim of this study was to investigate seawater intrusion to the suitability of the groundwater for oil palm cultivation at the ex-promontory land of Carey Island in Malaysia. This is the first study that used the integrated method of geo-electrical resistivity and hydrogeochemical methods to investigate seawater intrusion to the suitability of groundwater for oil palm cultivation at two different land cover condition. The relationship between earth resistivity, total dissolved solids and earth conductivity was derived with crop suitability classification according to salinity, used to identify water types and also oil palm tolerance to salinity. Results from the contour conductivity maps show that area facing severe coastal erosion and area still intact with mangrove forest exhibits unsuitable groundwater condition for oil palm at the unconfined aquifer thickness of 15 and 3 1 m, respectively. Based on local sea-level rise prediction and Ghyben-Herzherg assumption (sharp interface), the condition in the study area, especially in severe erosion area, by the twenty-first century will no longer be suitable for oil palm plantation. The application of geo-elechcal method combined with geochemical data, aided with the information on environmental history and oil palm physiography, has demonstrated that the integration of techniques is an effective tool in defining the status of agricultural suitability affected by salinity at the coastal aquifer area.
Integrated geoelectrical resistivity, hydrochemical and soil property analysis methods were used to study the groundwater characteristics of sandy soils within a shallow aquifer in the agriculture area, Machang. A pilot test investigation was done prior to the main investigation.
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