当社グループは 3,000 以上の世界的なカンファレンスシリーズ 米国、ヨーロッパ、世界中で毎年イベントが開催されます。 1,000 のより科学的な学会からの支援を受けたアジア および 700 以上の オープン アクセスを発行ジャーナルには 50,000 人以上の著名人が掲載されており、科学者が編集委員として名高い
。オープンアクセスジャーナルはより多くの読者と引用を獲得
700 ジャーナル と 15,000,000 人の読者 各ジャーナルは 25,000 人以上の読者を獲得
Yusi Shih
The most critical concerns during offshore wind turbine installation are wind conditions. Wind can cause safety issues and long periods of waiting, resulting in project delays and massive costs. The offshore wind energy industry relies on weather forecast reports, but the reports are frequently found to be inconsistent, particularly in wind speed.The decision to perform installation work is then difficult [1-15]. The current paper proposes a solution to analyse the similarity degree of the two reports, as well as predict the next opening of the weather window and its periodicity, by utilising the concept of time lag in Cross-Correlation and Pearson Correlation Coefficient. Not only must the reports be aligned, but wind types must also be precisely judged. The paper presents a new point of view .The most critical concerns during offshore wind turbine installation are wind conditions. Wind can cause safety issues and long periods of waiting, resulting in project delays and massive costs. The offshore wind energy industry relies on weather forecast reports, but the reports are frequently found to be inconsistent, particularly in wind speed. The decision to perform installation work is then difficult. The current paper proposes a solution to analyse the similarity degree of the two reports, as well as predict the next opening of the weather window and its periodicity, by utilising the concept of time lag in Cross-Correlation and Pearson Correlation Coefficient. Not only must the reports be aligned, but wind types must also be precisely judged. The paper presents a new point of view.