International Journal of Marine Science, 2025, Vol.15, No.1, 45-52 http://www.aquapublisher.com/index.php/ijms 47 analyze the changes in the speed of sound in seawater, draw the seabed topography through it, and even see some structures under the seabed. There is now a new method called self-organizing mapping (SOM), which is a nonlinear algorithm. It can handle relatively complex data relationships, and the results are more accurate than traditional linear algorithms (Li et al., 2021). 3.2 Machine learning and ai in inversion algorithm development Now, more and more research is using machine learning and artificial intelligence (AI) in inversion algorithms for ocean remote sensing. These technologies can find complex laws from massive data, so that the parameter inversion results are more accurate. For example, scientists use deep learning models to estimate effective wave heights based on the backscattering coefficient of the sea surface, and the results are very accurate (Wu et al., 2019). Some people also use machine learning methods to optimize the process of inverting water quality from satellite images, such as chlorophyll a concentration and water turbidity, which can also get good results (Zhu and Huang, 2021). 3.3 Challenges in inversion algorithm accuracy and validation Although inversion algorithms are becoming more and more advanced now, there are still many challenges in ensuring they are accurate and reliable. The performance of the algorithm depends heavily on data quality. The better and richer the data, the more stable the algorithm effect. Sometimes, if some additional observational data, such as on-site sampling data, can be added, not just rely on satellite images, the inversion results will usually be more accurate (Bisson et al., 2023). But the problem is that the marine environment is very complex. Not only are there algae in the water, but there are also many colored dissolved substances and non-algae particles. These will affect the inversion results and make the algorithm more difficult to do. So, we may need to develop more complex models to deal with these distractions. In order to verify whether an inversion algorithm is reliable, a large amount of field measurements are usually required and then compared with the existing standard model to ensure that the results are reliable (Zhao et al., 2022). 4 Applications of Inversion Algorithms in Ocean Studies 4.1 Monitoring ocean productivity and ecosystem health Inversion algorithms are very useful in understanding marine ecological situations. It can extract some important parameters from remote sensing data, such as how much chlorophyll is in the water, how clear the water is, etc. Commonly used algorithms now include semi-analytical algorithms (SAA) and absorption spectral decomposition algorithms (ADA). They can calculate the optical properties and types of absorbents in water from the data on seawater color (Zhao et al., 2022; Jin and Pan, 2024). With these algorithms, scientists can more accurately estimate chlorophyll concentration and transparency, thereby judging whether seawater is healthy and whether there are ecological changes. In addition, machine learning technology has also been added. It can further improve the inversion accuracy, allowing us to better monitor water quality and ecological vitality. 4.2 Ocean dynamics and climate studies Inversion algorithms are also helpful in studying ocean motion and climate change. For example, it can inversely deduce the sound speed profile (SSP) from remote sensing data from different sources. This parameter is important and can help us understand the acoustics and seawater flow underwater (Feng et al., 2024; Jiang and Wang, 2024). Some algorithms can also reconstruct clearer ocean color images, which is very critical for studying ocean motion and climate change in coastal waters (Yang et al., 2024). Some hybrid models will combine different types of remote sensing data, which will make the results more accurate and the image resolution higher. This way we can see more clearly how the ocean flows and how it has something to do with climate change (Kolluru et al., 2021). 4.3 Marine resource management and exploration Inversion algorithms are also used to manage and detect marine resources. We can use it to analyze the color of the ocean to determine whether there are fish in the water, or whether there are coral reefs in certain places. This is very helpful for both fisheries and ecological protection. In order to make the analysis results more accurate,
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