THE MACHINE LEARNING TECHNIQUE HAS BEEN DEVELOPED TO PREDICT VARIOUS PLASMA QUANTITIES INCLUDING TOTAL PLASMA DENSITY AND PLASMA WAVE AMPLITUDE IN EARTH'S MAGNETOSPHERE USING CONTROLLING INDICES. WE WILL EXTEND THIS TECHNIQUE TO PREDICT THE GLOBAL DISTRIBUTION OF WHISTLER MODE WAVES (CHORUS HISS MAGNETOSONIC WAVE) EMIC AND ULF WAVES USING SOLAR WIND PARAMETERS. THE SOLAR WIND PARAMETERS ARE AVAILABLE FROM THE OMNI DATA AND THE DATASET OF VARIOUS PLASMA WAVES AND ELECTRON DENSITY ARE AVAILABLE FROM THE THEMIS AND VAN ALLEN PROBES MEASUREMENTS. WE WILL USE THE VAN ALLEN PROBES OBSERVATION OF ENERGETIC ELECTRONS TO ANALYZE THE RADIATION BELT ELECTRON FLUX VARIATIONS. AFTER IDENTIFYING TYPICAL EVENTS SHOWING THE ELECTRON RESPONSE TO THE SOLAR WIND DRIVERS WE WILL SIMULATE THE RADIATION BELT FLUX EVOLUTION USING THE GLOBAL PLASMA WAVE DISTRIBUTION PREDICTED BY THE MACHINE LEARNING TECHNIQUE. THE UCLA 3D DIFFUSION CODE HAS BEEN DEVELOPED AND FULLY VALIDATED FOR SIMULATING THE ELECTRON EVOLUTION DUE TO RESONANT WAVE-PARTICLE INTERACTIONS. FOR COMPARISON WE WILL ALSO PERFORM THE RADIATION BELT SIMULATION USING THE EMPIRICAL PLASMA WAVE MODEL WHICH IS AVAILABLE FROM THE RECENT SATELLITE STATISTICS. THE SIMULATION RESULTS WILL BE VALIDATED AGAINST THE SATELLITE OBSERVATIONS USING VALIDATION METRICS.