Abstract
Data mining is the process of analyzing data from different perspectives and summarizing it into useful information. Data mining is applied to find patterns to help in the important tasks of medical diagnosis and treatment. In this paper, we present a sensor to measure water level in rivers, lakes, lagoons and streams. For such purpose and to prove our concept, we designed a pilot project through a micro-model that is constructed with a water level measurement sensor based on a simple open circuit that closes when in contact with water and experimentally tested into a water container under a controlled environment. The indicator for acidity, alkalinity, or basic is known as the PH value. A PH value of 7 means a substance is neutral. The lower value indicates acidity, and a higher value is a sign of alkalinity. Side effects that may occur after drugs are added to Bacteriostatic. Water includes fever, abscess formation, venous thrombosis or phlebitis, tissue death, and infections. We are going to implement weka tool to compare the time execution, frequency and an execution process by using a genetic algorithm. Here we used the Ultrasonic Sensor technique to measure the water level. Ultrasonic sensors are based on the measurement of the properties of acoustic waves with frequencies above the human audible range, often at roughly 40 kHz. They typically operate by generating a high-frequency pulse of sound, and then receiving and evaluating the properties of the echo pulse. In this study, the principle of water pinch technology, the optimization of water, steam allocation network have been studied and minimization of freshwater utility and wastewater generation in one of the petroleum refineries of Iran is taken into consideration. In order to research in this field and simplify the relevant calculations, an algorithm was developed and applied for reforming the network. Finally, the micro-model is tested by experimental tests under a controlled environment and satisfactory results are obtained. The experimental evaluation results showed a 99.2% of accuracy and which proves this mechanism effective and reliable in water optimization.
Highlights
A superstructure, which incorporates all feasible design alternatives for water treatment, reuse and recycle, is proposed. We formulate this structure as a non-convex Non-Linear Programming (NLP) problem, which is solved to global optimality
We presented the MEGA initiative for defining reference architecture for water management based on integrating IoT capabilities to achieve a scalable and feasible industrial system algorithm techniques are used to find out the time execution, frequency, accuracy and execution process of water management
High accuracy achieved through weka tool technique compare than R tool
Summary
Data Mining is a knowledge mining process It is an interdisciplinary subfield of computer science. It is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems. Average global water consumption within those sectors varies, and it depends of the development level of countries. In order to address the synthesis problems of separate and total water networks, different tools and methods have been proposed. It is important to mention that the synthesis problem of an overall or total water network is more complex, and this problem has been addressed fewer papers compared to the synthesis problem of separate networks (water using network or wastewater network)
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