ANALYSIS FROM 1980 TO 2018 OF TIDAL OBSERVATION DATA FOR ASSESSING THE STABILITY OF TIDAL CONSTANTS FOR PRIMARY PORT DOI

Barnabas O. Morakinyo

FUDMA Journal of Sciences, Journal Year: 2024, Volume and Issue: 8(6), P. 503 - 513

Published: Dec. 31, 2024

Tidal analysis involves the computation of tidal constants (phase lag (g) and amplitude (H)) constituents at a location. This study focuses on assessment stability g H for Bonny port which is only standard in Nigeria. Monthly observations was carried out with 1980, 1994 2018 year’s data using Least Squares Method (LSM) Harmonic Analysis MATLAB programming codes. The observation equation technique LSM adopted; dimension Normal (N) matrix equations obtained monthly 72 56 i.e. rows, columns. N inverted gave results mean sea level (MSL) 28 primary tide. Four major tide (M2, S2, K1 O1) remain stable throughout analysis. each year observed to be almost equal from three-year data. maximum residuals spreads computed over period show that are accurately analyze one-month can employed prediction several years. Therefore, it concluded M2, O1 type (F) semidiurnal since F 0.16 0.25.

Language: Английский

Su Dalga Enerjisi Üretimi ve Yapay Zekâ: Türkiye’nin Dünyadaki Yeri DOI
Selma Kaymaz, Tuğrul Bayraktar, Çağrı Sel

et al.

Yüzüncü Yıl Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Journal Year: 2024, Volume and Issue: 29(2), P. 798 - 822

Published: Aug. 20, 2024

Son yıllarda, sürdürülebilir bir dünya için yenilenemeyen enerji kaynaklarının kullanımının azaltılması gerekliliği giderek daha belirgin hale gelmektedir. Fosil yakıt tüketiminden, temiz enerjiye geçiş döneminde, yenilenebilir kaynakları hızla gelişme göstermektedir. Bu gelişmeler ışığında su enerjisi teknolojilerine odak artmaktadır. Enerji potansiyeli gerekli şartlar karşılandığı sürece; kaynaklı üretim projelerinin uygulanması ülkelerin refahına katkı sağlama taşımaktadır. Yenilenebilir üretiminde rekabete konu olan üretimi için; literatürde kıtalar arası enerjinin incelendiği, potansiyelinin ölçüldüğü, santraller uygun yer seçiminin yapıldığı, dalga – iklim ilişkisinin okyanus teknolojileri konularını içeren çalışmalarda geleneksel teknikler yanı sıra yapay zekâ tekniklerine de verilmektedir. Deneysel modelleme saha ölçüm tekniklerinin yüksek maliyetli olduğu, sayısal yöntemlerin parametre ve girdi hazırlık sürecinin zahmetli olması sebebiyle çeşitli yöntemleri, teknolojisinde yoğun şekilde kullanılmaktadır. Yapay sinir ağları da bu alanda karşılaşılan problemlerin çözümünde kullanılan tekniklerden birisi olarak almaktadır. derlemede, Asya Avrupa kıtasında hakkında yapılmış mevcut çalışmalardan bahsedilmekte, Türkiye’nin potansiyelini, literatür incelenerek ortaya konulmaktadır. Ayrıca tekniklerinden ağı metodunun teknolojilerinde ne hangi ölçüde kullanıldığı yöntemlerle ilgili literatüre verilmiştir.

Citations

0
A Novel Hybrid Model for Short-Term Traffic Flow Prediction Based on Spatio-Temporal Deep Learning with Considering Associated Factors Selection DOI Creative Commons

Yingping Tang,

Qiang Shang,

Longjiao Yin

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 128215 - 128234

Published: Jan. 1, 2024

Language: Английский

Citations

0
Significant wave height prediction in monsoon regions based on the VMD-CNN-BiLSTM model DOI Creative Commons

W. Shen,

Zongquan Ying,

Yiming Zhao

et al.

Frontiers in Marine Science, Journal Year: 2024, Volume and Issue: 11

Published: Nov. 25, 2024

A novel significant wave height prediction method for monsoon regions is proposed, utilizing the VMD-CNN-BiLSTM model to enhance accuracy under complex meteorological conditions. Traditional numerical models exhibit limitations in managing extreme marine conditions and fail fully integrate wind field information. Meanwhile, existing machine learning demonstrate insufficient generalization robustness long-term predictions. To address these shortcomings, predictive approach combines Variational Mode Decomposition (VMD) with a hybrid deep (CNN-BiLSTM). VMD employed decompose original sequence extract key features, while CNN captures spatial features of data. BiLSTM, turn, temporal dependencies. Experimental results reveal that provides substantial advantages performance across all seasons, including entire year. Compared traditional models, proposed demonstrates significantly reduced Mean Absolute Error (MAE) Root Square (RMSE), alongside an improved coefficient determination (R²). These findings confirm effectiveness reliability such as monsoons typhoons.

Language: Английский

Citations

0
Detection of breath sounds in speech: A deep learning approach DOI

K. Mohamed Ismail Yasar Arafath,

Aurobinda Routray

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 141, P. 109808 - 109808

Published: Dec. 17, 2024

Language: Английский

Citations

0
ANALYSIS FROM 1980 TO 2018 OF TIDAL OBSERVATION DATA FOR ASSESSING THE STABILITY OF TIDAL CONSTANTS FOR PRIMARY PORT DOI

Barnabas O. Morakinyo

FUDMA Journal of Sciences, Journal Year: 2024, Volume and Issue: 8(6), P. 503 - 513

Published: Dec. 31, 2024

Tidal analysis involves the computation of tidal constants (phase lag (g) and amplitude (H)) constituents at a location. This study focuses on assessment stability g H for Bonny port which is only standard in Nigeria. Monthly observations was carried out with 1980, 1994 2018 year’s data using Least Squares Method (LSM) Harmonic Analysis MATLAB programming codes. The observation equation technique LSM adopted; dimension Normal (N) matrix equations obtained monthly 72 56 i.e. rows, columns. N inverted gave results mean sea level (MSL) 28 primary tide. Four major tide (M2, S2, K1 O1) remain stable throughout analysis. each year observed to be almost equal from three-year data. maximum residuals spreads computed over period show that are accurately analyze one-month can employed prediction several years. Therefore, it concluded M2, O1 type (F) semidiurnal since F 0.16 0.25.

Language: Английский

Citations

0