This project entitled "FINDING WEATHER FORECASTING ACCURACY USING LINEAR REGRESSION", submitted by Arafartur Rahman Soikat, ID No G M FARADUZZAMAN, ID No and Md Al Amin, ID No to the Department of Computer Science and Engineering, Daffodil International University, has been accepted as satisfactory for partial fulfillment of the requirements for the degree of B.Sc. In this way, climatology learns experimentally about climate conditions and anticipates the future atmosphere. The vast majority of service organizations use temperature forecasts to assess what is to come.
One of the most pressing issues of the last decade is climate change and forecasting in general. Bangladesh ranks fifth among 170 countries most at risk from environmental change on the Global Climate Risk Index. To the north of the Himalayas is the ice sheet and the Bay of Bengal, which cannot be detected.
Motivation 03
In the event that this happens, the capital Dhaka, currently at the center of the nation, will have its own ocean rise (CCC, 2009) [3]. These strategies rely on the production of pseudo-sensory systems and pseudo-neural frameworks. Against free will, precipitation is sent out of the opposite (usually common) class.
In this chapter we describe related works, research summary, problem scope and challenges. Rejaur Rahman and Habibah Lateh they both are searching about weather forecast of Bangladesh and in this paper monthly base data and most extreme temperatures also, rainfall from many places in Bangladesh up to the period 1949-2013 and that was used and decomposed in this examination is provided by the Bangladesh Meteorological Department (BMD 2013). Currently, one of the most used methods for climate forecasting is information mining.
Raw data processing and equation calculations in this research were time-consuming. The Jupiter laptop is easy to use and learn, and is considered one of the best mining tools in real-time situations. Like this, the fourth row of the vapor graph shows that humidity is in relation to humidity, minimum temperature, maximum temperature, and precipitation.
We collect our data set from the perspective of Bangladesh weather and target 4 attributes of the data set and determine the forecast accuracy. The desire for temperature shows that in an hour when the average maximum temperature is 33 °C, the temperature shown will be 1.0 °C higher in Bangladesh by 2020, which was different from 1949. C (consistently 0.50 ° C), which will probably present problems to the general population in these parts of the country.
Spatial examples and the fluctuation of temperature and precipitation show that the northwestern, western and southwestern parts of the country are weaker to natural changes when it comes to rising temperatures. This assessment will not only help in displaying legitimate methodologies and expectations of combating the impact of natural changes in Bangladesh, but also help in understanding the nearby ecological changes in this part of South Asia. The results obtained are much better than the current strategy, demonstrating the correctness of the expectation through the direct relapse calculation.
Rationale of the Study 04
Research Questions 04
Expected Output 04
Get help on how we can calculate or achieve perfect weather forecast accuracy. The number of people who die each year due to accidents because they do not know in advance what will happen tomorrow.
Report Layout 05
BACKGROUND 6-9
- Related Works 06
- Comparative Analysis and Summary 08
- Scope of the Problem 08
- Challenges 09
This paper investigates the use of ANN model for month-to-month premise reliable climate observation with occasional debacle prediction. For predicted weather conditions using data mining to handle data and using some algorithms like Naïve Bayesian, Decision Tree etc. Present ECDF model for analysis monthly low and high temperature and represent statistical graph bar [6].
Linear regression, coefficient of variation, weighted inverse distance addition methods, and geologic data frames performed to investigate patterns, variability, and other patterns of temperature and precipitation. The moving autoregressive coordinated normal time regularization model was used to reproduce the temperature and precipitation information. To improve and find the accuracy of weather forecasting, make sure that the training accreditation training process is necessary.
Therefore, a multiplicative approach with aggregation function overcomes the difficulties of weather forecasting with additive approach. Accurate weather forecasts are essential for our everyday lives and have both a financial and environmental impact. Data mining method to dissect information factually and derive such guidelines that can be used for expectations.
Our data set has 65 years of smart weather station data and the data collection was very difficult. Not many works have been done with a wide investigation of information especially in the weather picture.
RESEARCH METHODOLOGY 10-16
Data Collection Procedure 10
Proposed Methodology 10
In this paper we use linear regression which is used in the Jupiter Notebook tool to analyze the accuracy of the data. We got the data from Kuggle (https://www.kaggle.com/emonreza/65-years-of-weather-data-bangladesh-preprocessed) which is open source for any kind of research project area. In this technological age there are various types of data mining tools that are used for data analysis.
When analyzing data for weather forecasting, we collect data from kuggle, which is open source for any research field. Based on the characteristics and their relationship from the data, Jupiter Notebook predicts possible attributes and possible assumptions for weather forecasting. Jupiter Notebook can analyze data directly from the dataset and react quickly to the result.
By using linear regression we can merge data in table and separate software from Jupiter Notebook. Linear regression works to create a relationship between two variables by fitting a linear equation to analyst data. The algorithm structure part shows us how linear regression works and how the output comes to it.
Linear regression analyzes data based on the structure of the data and the information provided in the data set. As can be seen in the figure, there is a relationship between precipitation humidity, minimum temperature, maximum temperature and precipitation amount. The first line of the graph in the figure shows the relationship between the amount of precipitation and humidity, the lowest temperature, the highest temperature and the amount of precipitation.
Here, the second row of this graph shows us a correlation between max temperature and humidity, min temperature, max temperature, precipitation.
IMPLEMENTATION AND RESULT ANALYSIS 17 -18
Linear Regression Algorithm Applying Procedure 17
7. We will approve our dataset, we will divide our information gathering into preparing and testing the dataset. We will use 80% of our information to train our dataset and 20% of our information will be used for testing the approval of our dataset. In this article, we discussed the last 64 years of environmental changes in Bangladesh based on temperature and precipitation data. The future desire for ecological change for the period 2013-2020 was examined and evidenced a particularly strong progression of natural change in Bangladesh, subject to changes in temperature and precipitation.
For example, if a strong overall external intensity of the climate occurs, such as a critical volcanic discharge, and this can be a good inspiration to discredit the measurement for that time. For the climate of Bangladesh, the temperature movements reflect a warming overall, and since 1949 the air in Bangladesh has warmed with a much higher movement of the general typical warming (0.20 vs 0.13 °C consistently). A significantly more vital increase is predicted for the mean of highest temperature (33.4 °C) than the mean of minimum temperature (21.14 °C).
The sample direction, significance and spatial patterns observed for both temperature and precipitation can similarly provide strong information about a risky environmental anomaly at a nearby/land level scale. Improved appreciation of advancing natural change helps to clarify the impact and shortcomings of the local people to carry out the most appropriate practices to adapt to ecological change and manage the changing condition in an unparalleled way. In this working atmosphere, chronic information is clearly used for the investigation of atmosphere information.
Md Rashid Mahmood, "A new approach for weather forecasting using forecast analysis and data mining techniques," ResearchGat, p. Rejaur Rahman1, "Climate change in Bangladesh: spatio-temporal analysis and simulation of recent temperature and precipitation data using GIS and time series analysis model,".
Experimental Result & Analysis 17
Description of Our Work 18
The proposed system can be used to check the temperature over the necessary time frame with the aim that the individual experts can take careful steps to maintain the loss of lives and property. The proposed structure uses modified straight backsliding approach to predict the temperature which has less deviation rate than what stands out from most data mining strategies such as clustering, backpropagation which gives up the additional features rather than measuring. The base temperature warmed more in the northern, northwestern, northeastern, central, and central southern parts, while the most extreme temperature warmed more in the southern, southeastern, and northeastern parts during the 1949-2013 period.
The accuracy of the least temperature is 86% and the relative stickiness accuracy in this paper is 67%. For perfect climate determination, we applied our proposed direct linear regression algorithm to the atmosphere dataset taken from an open source Kuggle atmosphere dataset from the official Kuggle website. To enhance the exploration, the perception is completed with Kuggle, a high-level data mining device that encourages direct access from datasets.
Daffodil International University 21 determines the relationship between the climatic parameters, such as temperature, wind speed, stickiness and so on, the correlation of the exhibition is done by direct linear regression algorithm to show the efficiency of our proposed cycle. We have chosen a rainfall forecasting method after analyzing a dataset of rainfall in Bangladesh, which is generated by some data mining techniques, such as first the analysis of the related relationship and then the application of regression analysis. We only use linear regression techniques; we can also support multiple regression, vector machines and artificial neural networks.
We can then make a comparison about which algorithm is the best fit for our data. In the future, we can improve our system by adding many more factors to wind speed, cloud cover and bright sunshine forecasts and make our projects more accurate at weather forecasting.
