Chemical　moderate　preoxidation　for　algae-laden　water　is　an　economical　and　prospective　strategy　for　controlling　algae　and　exogenous　pollutants,　whereas　it　is　constrained　by　a　lack　of　effective　on-line　evaluation　and　quick-response　feedback　method.　Herein,　excitation-emission　matrix　parallel　factor　analysis　(EEM-PARAFAC)　was　used　to　identify　cyanobacteria　fluorophores　after　preoxidation　of　sodium　hypochlorite　(NaClO)　at　Excitation/Emission　wavelength　of　260(360)/450　nm,　based　on　which　the　algal　cell　integrity　and　intracellular　organic　matter　(IOM)　release　were　quantitatively　assessed.　Machine　learning　modeling　of　fluorescence　spectral　data　for　prediction　of　moderate　preoxidation　using　NaClO　was　established.　The　optimal　NaClO　dosage　for　moderate　preoxidation　depended　on　algal　density,　growth　phases,　and　organic　matter　concentrations　in　source　water　matrices.　Low　doses　of　NaClO　(＜0.5　mg/L)　led　to　short-term　desorption　of　surface-adsorbed　organic　matter　(S-AOM)　without　compromising　algal　cell　integrity,　whereas　high　doses　of　NaClO　(＞=　0.5　mg/L)　quickly　caused　cell　damage.　The　optimal　NaClO　dosage　increased　from　0.2-0.3　mg/L　to　0.9-1.2　mg/L,　corresponding　to　the　source　water　with　algal　densities　from　0.1　x　10(6)　to　2.0　x　10(6)　cells/mL.　Different　growth　stages　required　varying　NaClO　doses:　stationary　phase　cells　needed　0.3-0.5　mg/L,　log　phase　cells　0.6-0.8　mg/L,　and　decaying　cells　2.0-2.5　mg/L.　The　presence　of　natural　organic　matter　and　S-AOM　increased　the　NaClO　dosage　limit　with　higher　dissolved　organic　carbon　(DOC)　concentrations　(1.00　mg/L　DOC　required　0.8-1.0　mg/L　NaClO,　while　2.20　mg/L　DOC　required　1.5-2.0　mg/L).　Compared　to　other　predictive　models,　the　machine　learning　model　(Gaussian　process　regression-Matern　(0.5))　performed　best,　achieving　R-2　values　of　1.000　and　0.976　in　training　and　testing　sets.　Optimal　preoxidation　followed　by　coagulation　effectively　removed　algal　contaminants,　achieving　91%,　92%,　and　92%　removal　for　algal　cells,　turbidity,　and　chlorophyll-a,　respectively,　thereby　demonstrating　the　effectiveness　of　moderate　preoxidation.　This　study　introduces　a　novel　approach　to　dynamically　adjust　NaClO　dosage　by　monitoring　source　water　qualities　and　tracking　post-preoxidation　fluorophores,　enhancing　moderate　preoxidation　technology　application　in　algae-laden　water　treatment.