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161
Flow chart diagram of blind quantum algorithm.
Published 2024“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”
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Rosenbrock function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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166
Rosenbrock function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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167
Levy function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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168
Rastrigin function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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169
Levy function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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170
Rastrigin function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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171
Levy function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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172
Levy function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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173
Rastrigin function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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174
Rastrigin function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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175
Rosenbrock function losses for .
Published 2025“…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …”
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176
Flow chart diagram of quantum hash function.
Published 2024“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”
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177
Sensor value scenario for fuzzy logic algorithm.
Published 2025“…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. …”
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178
Type-1 membership function for distance.
Published 2025“…<div><p>In this study, we present an algorithm to estimate the distance between a vehicle and a target object using light from headlights captured by a camera. …”
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179
Type-1 membership function for speed.
Published 2025“…<div><p>In this study, we present an algorithm to estimate the distance between a vehicle and a target object using light from headlights captured by a camera. …”
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180