Comparative Study on Soft Computing Approach in Weather Forecasting: Analytical Essay
Abstract– In a developing country, like India where the agriculture & industries are base for the national economy, the weather conditions play leading role for their proper development and smooth running. Therefore having accurate weather forecasting information may allow farmers or industry managers to make better decisions on managing their farms. Soft computing using ANN is an innovative approach to construct a computationally intelligent system that is able to process nonlinear weather conditions within a specific domain, and make prediction. A number of researches have been done or being done using Soft Computing Approach for forecasting. In this paper the presentation is all about to present the comparative study of several researches and some key findings that are initials for better start any soft computing model for prediction.
Keywords– Soft Computing, Artificial Neural Network (ANN), Back Propagation Algorithms, Multilayer Feed Forward Neural network (MLFFNN), Mean Square Error (MSE).
Soft Computing is an efficient approach for forecasting, whether it is weather forecasting or any other else. A number of researches have been done focusing on the usefulness of soft computing approach in forecasting area. Here the presentation is utilizing some of researches to make some conclusions that are initials to be taken in account when planning forecasting using ANN technique. In traditional Weather forecasting approaches like:
The first approach is based upon the occurrence of analogues and is often referred to by meteorologists as analogue forecasting. This approach is useful for predicting local-scale weather if recorded cases are plentiful. The second approach is based upon the equations and forward simulations of the atmosphere, and is often referred to as computer modeling. Because of the grid Coarseness, the dynamical approach is only useful for modeling large-scale weather phenomena and may not predict short-term weather efficiently. But for local scale & short term weather forecasting the approach of artificial neural networks (ANNs) is so efficient and a little bit easy.
ANNs provide a methodology for solving many types of non-linear problems that are difficult to solve by traditional techniques. Most meteorological processes often exhibit temporal and spatial variability, and are further plagued by issues of non-linearity of physical processes, conflicting spatial and temporal scale and uncertainty in parameter estimates. With ANNs, there exists the capability to extract the relationship between the inputs and outputs of a process, without the physics being explicitly provided. Thus, these properties of ANNs are well suited to the problem of weather forecasting under consideration. The popular soft computing techniques is ANN which performs nonlinear mapping between inputs and outputs, has lately provided alternative approaches to weather forecasting and so many researchers have taken in their research and come into the conclusion that ANN is best suited for forecasting. In the following paper the main objective is to find out some basic fundamentals and initials to make conventions about the ANN & forecasting.
Figure 1: Schematic diagram of data acquisition system
To summarize the working of our system we can categorize the major components in following manner:
The experimental setup consists of highly sensitive atmospheric pressure sensor and atmospheric temperature sensor . We have linked the sensors to the data logging computer using an interface cable to the parallel port LPT1. Data acquisition software records data in real time at a fixed time intervals of 4 seconds. Data precision for pressure sensor is 1 mbar and for temperature sensor is 0.1℃. System has capability to record the data continuously for several days without break in data recording.
We considered atmospheric pressure as a primary parameter and atmospheric temperature and relative humidity secondary type. Other parameters are also considered like wind direction and wind velocity.
Atmospheric pressure changes at any given place on earth are minute, hence, a very high sensitivity of pressure sensor is essential. Atmospheric pressure also changes with altitude and hence base atmospheric pressure differs from place to place depending on the altitude of the place from mean sea level. User requirement involves the collection of different input values and variables; including the selection of one or more forecasting measurements, the forecasting range, parameters such as the local forecast and distance of altitude from the sea level, and no. of samples per recording and interval of recording.
Having collected and preprocessed all of the relevant weather information, our system starts the appropriate network training and forecasting, which is based on the back propagation in a neuro-fuzzy network. Table I shows the different categories defined for the fuzzification of the weather conditions.
The fuzzy data for predicting the occurrence of either rain or not rain ,bad weather ,good weather are based on the above given table I. While local pressure is measured in absolute scale , for simplicity of understanding of weather conditions pressure at sea level is computer with altitude information as correction factor to predict weather .
The following conditions are to be analyzed —
From recorded pressure data the generated weather forecast under stable low-pressure condition was rainy weather. As only two hours record was used for testing, we did not expect great results from it. Pressure changes recorded at fixed pressure rate of -0.564 mbar/h. It is very small change and is considered to be constant.
After going through the above detailed study we find the following key results that play a major role in any forecasting model building. Apart from the traditional forecasting systems, ANN based forecasting is much feasible & best suited. Applying soft computing could be one of the best alternatives for local and short scale weather forecasting. The Study says any forecasting system using Artificial Neural Network & Back propagation Algorithms depends on following:
Figure 2: Architecture of an ANN based model
In the Above shown figure 1 Inputs can be Temperature, Rain, Wind, Humidity, etc.
From conducted experiments we find the following key changes in the atmospheric pressure signature that can be related to dynamic states of atmospheric conditions and for meaningful short duration weather prediction. We are noticed the following key features in atmospheric pressure patterns that were related to the weather conditions and indicated trend of the future weather of the place. These conditions were:
These trends were actually found in the recorded data and the selection of August month for the experiments was benefiting, as there were almost all types of signatures present in the atmospheric pressure indicating weather changes.
Experiments were carried out on different locations of the different city. The performance of the experiments from stations having short difference from the sea level in the form of altitude is the best. These observations were carried out on the time series basis. The results for a single station or multiple stations do not produce a large difference in performance. The best result that is achieved by our model is due to the availability of a large amount of input data for the model to select the right variables. Thus the model has a greater chance of producing better prediction results .It is found and can be deduced that the correlation between the data at time t and t+1 is high; therefore, it is easier to build a successful model.
After going through all the above study & discussion we see that applying soft computing model for forecasting the weather conditions is most feasible rather than any other short term & local based weather forecasting approach. Through the implementation of this system, we illustrate how an intelligent system can be efficiently integrated with a neuro-Fuzzy prediction model to implement an online weather information retrieval, analysis, and prediction system by using electronic sensors. Increasing parameters for weather modeling may help in predicting weather changes to greater extend in comparison with than simple model used in present case.
Introduction One of the most important thing for humankind it to plan their day, to plan their day human need to know about the weather forecasting so they can plan their day or even their month accordingly, as said wiki: “Weather forecasting is the application of science and technology to predict the conditions of the atmosphere for a given place and time’. from a long way back weather forecasting always play a big role in humanity. Before to predict the...
Introduction “Weather” is defined as the the condition of the atmosphere at a specific space and time as regards heat, dryness, wind, rain, etc. over a short time frame, whereas “climate” refers to the weather data of a place over a longer period to yield meaningful averages.”Global Change” means alterations in the Earth. A Brief History Man has always aspired to predict about the weather conditions. In the past, astrologers studied stars and dreams to predict weather and much more....
Agriculture is one field of the human activity which is extremely sensitive to weather and climate. The study of these two aspects in relation to agriculture is referred as agricultural meteorology and is a multidisciplinary science. Agricultural meteorology when properly applied by plant scientists can achieve the sustainability of agricultural production system through efficient management of agro-climatic resources and crop microclimate modification. Each and every plant developmental phase is decided by meteorological parameters. Every genotype has its own optimum climatic...
Introduction Weather is an uncontrollable atmospheric action and often inconsistent. Can the same be said about our moods? Some people’s moods are like the weather, hot, cold and very inconsistent. Studies have been done to see if one is dependent of the other. Weather has for some time been believed to impact a person’s mood but it is very difficult to capture in a study. This could be due to how people describe their mood on self-reporting surveys or weather...
Weather is a short-term climate change. While it is sunny today, it can be rainy, even stormy the next day. There are a lot of weather conditions in the world and these conditions are considered to have some effects on people’s mood. (Widmer, Bill, “Lifehack”) Unlike some people who are the opposite of this idea, I agree with it. The weather has a lot of effects on people’s mood. There is some relationship between life satisfaction and weather conditions, for...
In a Pilots career, they will encounter many different circumstances that require quick thinking and proper judgement, this is regarded as Decision Making. Circumstances such as poor weather require pilots to react and make a decision based on the environment around them. Pilots are required to provide adequate judgement calls for the safety of themselves and crew onboard. There is no secret that experience plays a significant role in decision making, decision making can be broken down into different categories...
Introduction Aviation has a high level of safety for commercial operations and is considered as one of the safest modes of transport today. Although the aviation industry is considered a safe mode of transport there are accidents that occur due to many different factors. This includes factors such as air traffic control, maintenance and human factors. Another factor that that contributes is the weather, with many different weather phenomenon, weather is a dangerous factor that results in some fatal crashes...
Abstract An individual sees approximately 3000 ads per day and the number is not likely to reduce anytime soon. Hence we explore the various effects of advertising strategies employed on the individual. It addresses the various forms of advertisements that an individual is exposed to in their day-to-day lives as well as the effects of the various persuasive psychological techniques on the psyche of the individual. These include the use of color, heuristics, emotional conditioning, and personalization in advertisements. It...
Executive summary This study will focus on investigating and identifying the relationship between strategies and property tax collection in Tanzania. Specifically, it aims at examining the strategies for the improvement of property tax collection in government, identifying the major challenges confronting property tax collection, and suggests possible measures to overcome those challenges to increase revenue collection from the property owners. The study intends to involve 120 respondents from 4 wards of Ngaramtoni Township Authority at TRA-Arumeru in Arusha, Tanzania. The...
01 / 09
Fair Use Policy
EduBirdie considers academic integrity to be the essential part of the learning process and does not support any violation of the academic standards. Should you have any questions regarding our Fair Use Policy or become aware of any violations, please do not hesitate to contact us via email@example.com.
We are here 24/7 to write your paper in as fast as 3 hours.