scholarly journals Prediction Research of Red Tide Based on Improved FCM

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaomei Hu ◽  
Dong Wang ◽  
Hewei Qu ◽  
Xinran Shi
Keyword(s):  
Objective Function ◽  
Red Tide ◽  
Marine Ecosystem ◽  
Prediction Algorithm ◽  
Cluster Center ◽  
Red Tides ◽  
Fcm Algorithm ◽  
Initial Cluster ◽  
Data Density ◽  
Fuzzy State

Red tides are caused by the combination effects of many marine elements. The complexity of the marine ecosystem makes it hard to find the relationship between marine elements and red tides. The algorithm of fuzzyc-means (FCM) can get clear classification of things and expresses the fuzzy state among different things. Therefore, a prediction algorithm of red tide based on improved FCM is proposed. In order to overcome the defect of FCM which is overdependent on the initial cluster centers and the objective function, this paper gains the initial cluster centers through the principle of regional minimum data density and the minimum mean distance. The feature weighted cluster center is added to the objective function. Finally, the improved FCM algorithm is applied in the prediction research of red tide, and the results show that the improved FCM algorithm has good denoising ability and high accuracy in the prediction of red tides.

scholarly journals Feeding diverse prey as an excellent strategy of mixotrophic dinoflagellates for global dominance

2021 ◽  
Vol 7 (2) ◽  
pp. eabe4214
Author(s):  
Hae Jin Jeong ◽  
Hee Chang Kang ◽  
An Suk Lim ◽  
Se Hyeon Jang ◽  
Kitack Lee ◽  
...  
Keyword(s):  
Genetic Factor ◽  
Red Tide ◽  
Biogeochemical Cycles ◽  
Evolutionary Strategy ◽  
Distribution Data ◽  
Red Tides ◽  
Trade Off ◽  
Moderate Growth ◽  
Prey Diversity ◽  
Standing Question

Microalgae fuel food webs and biogeochemical cycles of key elements in the ocean. What determines microalgal dominance in the ocean is a long-standing question. Red tide distribution data (spanning 1990 to 2019) show that mixotrophic dinoflagellates, capable of photosynthesis and predation together, were responsible for ~40% of the species forming red tides globally. Counterintuitively, the species with low or moderate growth rates but diverse prey including diatoms caused red tides globally. The ability of these dinoflagellates to trade off growth for prey diversity is another genetic factor critical to formation of red tides across diverse ocean conditions. This finding has profound implications for explaining the global dominance of particular microalgae, their key eco-evolutionary strategy, and prediction of harmful red tide outbreaks.

scholarly journals High Spatial-Resolution Red Tide Detection in the Southern Coast of Korea Using U-Net from PlanetScope Imagery

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4447
Author(s):  
Jisun Shin ◽  
Young-Heon Jo ◽  
Joo-Hyung Ryu ◽  
Boo-Keun Khim ◽  
Soo Mee Kim
Keyword(s):  
Deep Learning ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Red Tide ◽  
Learning Approaches ◽  
Red Tides ◽  
Southern Coast ◽  
Color Sensors ◽  
Deep Learning Model ◽  
Bloom Water

Red tides caused by Margalefidinium polykrikoides occur continuously along the southern coast of Korea, where there are many aquaculture cages, and therefore, prompt monitoring of bloom water is required to prevent considerable damage. Satellite-based ocean-color sensors are widely used for detecting red tide blooms, but their low spatial resolution restricts coastal observations. Contrarily, terrestrial sensors with a high spatial resolution are good candidate sensors, despite the lack of spectral resolution and bands for red tide detection. In this study, we developed a U-Net deep learning model for detecting M. polykrikoides blooms along the southern coast of Korea from PlanetScope imagery with a high spatial resolution of 3 m. The U-Net model was trained with four different datasets that were constructed with randomly or non-randomly chosen patches consisting of different ratios of red tide and non-red tide pixels. The qualitative and quantitative assessments of the conventional red tide index (RTI) and four U-Net models suggest that the U-Net model, which was trained with a dataset of non-randomly chosen patches including non-red tide patches, outperformed RTI in terms of sensitivity, precision, and F-measure level, accounting for an increase of 19.84%, 44.84%, and 28.52%, respectively. The M. polykrikoides map derived from U-Net provides the most reasonable red tide patterns in all water areas. Combining high spatial resolution images and deep learning approaches represents a good solution for the monitoring of red tides over coastal regions.

A Red Tide of Gyrod Inium Aurelum in Sea Lochs of the Firth of Clyde and Associated Mortality of Pond-Reared Salmon

1982 ◽  
Vol 62 (4) ◽  
pp. 771-782 ◽  
Author(s):  
K. J. Jones ◽  
P. Ayres ◽  
A. M. Bullock ◽  
R. J. Roberts ◽  
P. Tett
Keyword(s):  
Osmotic Shock ◽  
Red Tide ◽  
Clinical Signs ◽  
Cellular Damage ◽  
Fish Ponds ◽  
Red Tides ◽  
Gymnodinium Breve ◽  
The North ◽  
Cell Densities ◽  
Gyrodinium Aureolum

Red tides of the naked dinoflagellate Gyrodinium aureolum Hulburt occurred in sealochs in the north of the Firth of Clyde, Scotland, during late September 1980. Greatestconcentrations of the organism were found in the top 1 m layer of the water column, which was stabilized, and probably also enriched with nutrients, by freshwater input fromland drainage. In addition vertical and horizontal concentration must be postulated toexplain Gyrodinium cell densities of 2 x to7 cells I"1 and chlorophyll concentrations of 2228 mg m“”3 near the shore at Otter Ferry, Loch Fyne.On 28 September 1980, water containing the red tide at Otter Ferry was unintentionally pumped into fish ponds at a shore-based salmon farm and resulted in the death, in one pond, of 3000 salmon each weighing about 1 kg and of 200–300 smolts in another when water was transferred to it from the affected pond. Pathological investigation of affected salmon showed that death was likely to have resulted from asphyxiation and osmotic shock as a result of extensive cellular damage to gills and guts. Results of mouse bioassays, using acidic and ether extracts of flesh and guts from affected salmon, suggest that necrotizing toxin(s) was associated with the cells of Gyrodinium aureolum during the bloom. The clinical signs exhibited by mice injected with toxin extracts were, however, unlike those caused by paralytic shellfish poison or toxins of the Gymnodinium breve type.

Fuzzy C-Means in High Dimensional Spaces

2013 ◽  
pp. 1-16
Author(s):  
Roland Winkler ◽  
Frank Klawonn ◽  
Rudolf Kruse
Keyword(s):  
Objective Function ◽  
Local Minimum ◽  
High Dimensional ◽  
Controlled Environment ◽  
Data Sets ◽  
Local Minima ◽  
High Dimensions ◽  
Data Set ◽  
Fcm Algorithm ◽  
Centre Of Gravity

High dimensions have a devastating effect on the FCM algorithm and similar algorithms. One effect is that the prototypes run into the centre of gravity of the entire data set. The objective function must have a local minimum in the centre of gravity that causes FCM’s behaviour. In this paper, examine this problem. This paper answers the following questions: How many dimensions are necessary to cause an ill behaviour of FCM? How does the number of prototypes influence the behaviour? Why has the objective function a local minimum in the centre of gravity? How must FCM be initialised to avoid the local minima in the centre of gravity? To understand the behaviour of the FCM algorithm and answer the above questions, the authors examine the values of the objective function and develop three test environments that consist of artificially generated data sets to provide a controlled environment. The paper concludes that FCM can only be applied successfully in high dimensions if the prototypes are initialized very close to the cluster centres.

scholarly journals Weighted k-Prototypes Clustering Algorithm Based on the Hybrid Dissimilarity Coefficient

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ziqi Jia ◽  
Ling Song
Keyword(s):  
Categorical Data ◽  
Clustering Algorithm ◽  
Numerical Data ◽  
Experimental Results ◽  
Cluster Center ◽  
Real Dataset ◽  
Dissimilarity Coefficient ◽  
Initial Cluster ◽  
Data Objects ◽  
Selection Of

The k-prototypes algorithm is a hybrid clustering algorithm that can process Categorical Data and Numerical Data. In this study, the method of initial Cluster Center selection was improved and a new Hybrid Dissimilarity Coefficient was proposed. Based on the proposed Hybrid Dissimilarity Coefficient, a weighted k-prototype clustering algorithm based on the hybrid dissimilarity coefficient was proposed (WKPCA). The proposed WKPCA algorithm not only improves the selection of initial Cluster Centers, but also puts a new method to calculate the dissimilarity between data objects and Cluster Centers. The real dataset of UCI was used to test the WKPCA algorithm. Experimental results show that WKPCA algorithm is more efficient and robust than other k-prototypes algorithms.

Fuzzy C-Means in High Dimensional Spaces

2011 ◽  
Vol 1 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Roland Winkler ◽  
Frank Klawonn ◽  
Rudolf Kruse
Keyword(s):  
Objective Function ◽  
Local Minimum ◽  
High Dimensional ◽  
Controlled Environment ◽  
Data Sets ◽  
Local Minima ◽  
High Dimensions ◽  
Data Set ◽  
Fcm Algorithm ◽  
Centre Of Gravity

High dimensions have a devastating effect on the FCM algorithm and similar algorithms. One effect is that the prototypes run into the centre of gravity of the entire data set. The objective function must have a local minimum in the centre of gravity that causes FCM’s behaviour. In this paper, examine this problem. This paper answers the following questions: How many dimensions are necessary to cause an ill behaviour of FCM? How does the number of prototypes influence the behaviour? Why has the objective function a local minimum in the centre of gravity? How must FCM be initialised to avoid the local minima in the centre of gravity? To understand the behaviour of the FCM algorithm and answer the above questions, the authors examine the values of the objective function and develop three test environments that consist of artificially generated data sets to provide a controlled environment. The paper concludes that FCM can only be applied successfully in high dimensions if the prototypes are initialized very close to the cluster centres.

scholarly journals Tracing the sources of nutrients fueling dinoflagellate red tides occurring along the coast of Korea using radium isotopes

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hyeong Kyu Kwon ◽  
Guebuem Kim ◽  
Yongjin Han ◽  
Junhyeong Seo ◽  
Weol Ae Lim ◽  
...  
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Red Tide ◽  
Subsurface Layer ◽  
Vertical Mixing ◽  
Eastern Coast ◽  
Nutrient Concentrations ◽  
Red Tides ◽  
Radium Isotopes ◽  
Nutrient Sources

Abstract It is a well held concept that the magnitude of red-tide occurrence is dependent on the amount of nutrient supply if the conditions are same for temperature, salinity, light, interspecific competition, etc. However, nutrient sources fueling dinoflagellate red-tides are difficult to identify since red tides usually occur under very low inorganic-nutrient conditions. In this study, we used short-lived Ra isotopes (223Ra and 224Ra) to trace the nutrient sources fueling initiation and spread of Cochlodinium polykrikoides blooms along the coast of Korea during the summers of 2014, 2016, and 2017. Horizontal and vertical distributions of nutrient concentrations correlated well with 224Ra activities in nutrient-source waters. The offshore red-tide areas showed high 224Ra activities and low-inorganic and high-organic nutrient concentrations, which are favorable for blooming C. polykrikoides in competition with diatoms. Based on Ra isotopes, the nutrients fueling red-tide initiation (southern coast of Korea) are found to be transported horizontally from inner-shore waters. However, the nutrients in the spread region (eastern coast of Korea), approximately 200 km from the initiation region, are supplied continuously from the subsurface layer by vertical mixing or upwelling. Our study highlights that short-lived Ra isotopes are excellent tracers of nutrients fueling harmful algal blooms in coastal waters.

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