Weather casting with Machine Learning (SVM and SRNN).
Dependencies: EthernetInterface GraphicHandler NTPClient SRNN SVM SensorModule mbed-rtos mbed
share.hpp@1:8538381cae81, 2015-02-16 (annotated)
- Committer:
- yukari_hinata
- Date:
- Mon Feb 16 07:53:45 2015 +0000
- Revision:
- 1:8538381cae81
- Parent:
- 0:f6cdb984f638
- Child:
- 2:20ecfe6edd71
changed.
Who changed what in which revision?
User | Revision | Line number | New contents of line |
---|---|---|---|
yukari_hinata | 0:f6cdb984f638 | 1 | #ifndef SHARE_H_INCLUDED |
yukari_hinata | 0:f6cdb984f638 | 2 | #define SHARE_H_INCLUDED |
yukari_hinata | 0:f6cdb984f638 | 3 | |
yukari_hinata | 1:8538381cae81 | 4 | #define PREDICT_LENGTH (3) // 予測系列長 |
yukari_hinata | 1:8538381cae81 | 5 | #define PREDICT_INTERVAL_TIME (1 * 60 * 60) // 予測間隔 : 1h |
yukari_hinata | 1:8538381cae81 | 6 | #define LEN_DATA_SEQUENCE (100) // 観測データの履歴長 |
yukari_hinata | 1:8538381cae81 | 7 | #define NUM_WEATHERS (4) // 気候の種類 |
yukari_hinata | 1:8538381cae81 | 8 | #define DIM_SIGNAL (3) // 信号の次元(=センサの数) |
yukari_hinata | 1:8538381cae81 | 9 | #define MCSVM_NUM_SAMPLES (200) // MCSVMのサンプル数 |
yukari_hinata | 1:8538381cae81 | 10 | |
yukari_hinata | 1:8538381cae81 | 11 | |
yukari_hinata | 0:f6cdb984f638 | 12 | // 天候を表す列挙型 |
yukari_hinata | 0:f6cdb984f638 | 13 | typedef enum { |
yukari_hinata | 0:f6cdb984f638 | 14 | SHINY = 0, // 晴れ |
yukari_hinata | 0:f6cdb984f638 | 15 | CLOUDY = 1, // 曇 |
yukari_hinata | 0:f6cdb984f638 | 16 | RAINY = 2, // 雨 |
yukari_hinata | 0:f6cdb984f638 | 17 | SNOWY = 3, // 雪 |
yukari_hinata | 0:f6cdb984f638 | 18 | } WEATHER_STATUS; |
yukari_hinata | 0:f6cdb984f638 | 19 | |
yukari_hinata | 0:f6cdb984f638 | 20 | #endif /* SHARE_H_INCLUDED */ |