ベンチャ`悶Y垢型3
牽uの住宥i嵳ビッグデ`タにLれたパタ`ンをkする仟たなパタ`ンマイニングモデルの_k
- Japan Road Transportation Information Center (JARTIC) has set up the sensor network to monitor traffic congestion in Fukushima.
- Each road-segment in this network generates data at every 5-minute interval.
- Previous year, we have developed a data warehouse technology that generates data frames at 10 times faster than the state-of-the-art.
- This year, we plan to develop a novel pattern algorithm to discover hidden patterns.
シラバス

2023定4埖

4埖10晩
娩I坪否 Introduction to Fukushima Traffic Congestion System. Learn to extract the data and understand the format of data collected.

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4埖24晩
娩I坪否Processing the data and converting the Japan geographical information into world geographical format.

2023定5埖

5埖1晩
娩I坪否 Preprocessing the collected Fukushima congestion data and applying Linear regression to predict the future congestion values.

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5埖15晩
娩I坪否Evaluating the error rate and exploring different machine learning models to decrease the error in prediction.

2023定6埖

6埖5晩
娩I坪否 Conducting the time series analysis on the Fukushima traffic congestion data.

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6埖19晩
娩I坪否 Converting Fukushima traffic congestion database into row format and performing pattern mining algorithms from PAMI to mine the frequent patterns in the data.

2023定7埖

7埖3晩
娩I坪否Converting Fukushima-Traffic congestion data in multiple time series using fuzzy logic. And understanding the statistics of the data.

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7埖24晩
娩I坪否Mining partial periodic patterns from multiple fuzzy time series data and visualizing the patterns on QGIS to find which areas are facing the traffic congestion with respected to time instances.

2023定10埖

10埖10晩
娩I坪否Preprocessing the collected Fukushima congestion data by JARDIC system and removing NaN values.

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10埖16晩
娩I坪否How to use JARDIC system . From the obtained prepocessed data converting it into one Big Database

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2023定11埖

11埖1晩
娩I坪否Understanding Different datatypes of Jartic System and visualizing sensor network using QGIS.

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11埖20晩
娩I坪否Applying frequent pattern mining technique to find the frequent congested areas using PAMI.Visualizing the resultant frequent congested areas using QGIS.

2023定12埖

12埖18晩
娩I坪否Understanding Air Pollution Database and removing the high pollution sensors and less pollution sensors which are no useful.

12埖21晩
娩I坪否Implementing Different algorithms and pointing out the outliers for the data using one class svm , Local outlier factor, Minimum covariance determinant.

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2024定1埖

1埖8晩
娩I坪否After Finding outliers using Imputations. Now the next step is to find the Hourly data in units of time.

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1埖15晩
娩I坪否By taking Hourly Data into consideration . Again By applying Imputation techniques we will find the outliers.

1埖22晩
娩I坪否By using hourly data we will apply Fuzzy alogithm to locate the safe places to live and harmful places also we can detect from the data.

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