Gorilla Troops and the Traveling Salesman Problem: A Bio-Inspired Optimization Approach This study introduces a gorilla-inspired metaheuristic algorithm to solve the Traveling Salesman Problem (TSP). By modeling exploration, migration, and leadership dynamics observed in gorilla troops, the method balances global search and local exploitation. visit:  aidatascientits.com Nominate:  https://aidatascientists.com/ award-nomination/?ecategory= Awards&rcategory=Awardee Contact:  support@aidatascientists.com #worldresearchawards #researchawards #AcademicAwards #ScienceAwards #ArtificialIntelligence #TravelingSalesmanProblem #Metaheuristics #OptimizationTheory

 Unconditionally Stable Gradient Flows via Hyperbolic Tangent SAV Schemes This work develops an unconditionally energy-stable numerical scheme for gradient flow models using a hyperbolic tangent–based Scalar Auxiliary Variable (SAV) reformulation. Through variational principles, functional analysis, and time-discretization techniques, the method ensures unconditional stability and high accuracy. visit:  aidatascientits.com Nominate:  https://aidatascientists.com/ award-nomination/?ecategory= Awards&rcategory=Awardee Contact:  support@aidatascientists.com #worldresearchawards #researchawards #AcademicAwards #ScienceAwards #ArtificialIntelligence #GradientFlows #SAVMethod #NumericalAnalysis  #ScientificComputing #PhaseFieldModels

 Semi-Supervised Deep Matrix Factorization for Multi-Omics Clustering This study proposes a semi-supervised deep matrix factorization (SSDMF) model for integrative multi-omics clustering. By combining nonnegative matrix factorization, manifold regularization, and deep representation learning, the framework captures shared and modality-specific structures across genomic, transcriptomic, and proteomic datasets. visit:  aidatascientits.com Nominate:  https://aidatascientists.com/ award-nomination/?ecategory= Awards&rcategory=Awardee Contact:  support@aidatascientists.com #worldresearchawards #researchawards #AcademicAwards #ScienceAwards #ArtificialIntelligence #MultiOmics #MatrixFactorization #DeepLearning #Bioinformatics

  Modeling Europe’s Water Conflicts Through AI and Game Theory This study applies mathematical modeling, hydrological simulations, and game-theoretic analysis to assess water allocation conflicts across Europe. Using optimization algorithms and AI-based predictive analytics, the framework evaluates adaptation efficiency under climate variability scenarios. visit:  aidatascientits.com Nominate:  https://aidatascientists.com/ award-nomination/?ecategory= Awards&rcategory=Awardee Contact:  support@aidatascientists.com #worldresearchawards #researchawards #AcademicAwards #ScienceAwards #ArtificialIntelligence #WaterManagement #GameTheory #ClimateAdaptation

 Physics-Informed Gated Neural Networks for Differential Equation Solvers This research introduces a physics-informed gated neural network (PIGNN) framework for solving ordinary and partial differential equations. By embedding governing physical laws directly into the loss function and incorporating gating mechanisms for adaptive feature control, the model improves convergence, generalization, and numerical stability. visit: aidatascientits.com Nominate: https://aidatascientists.com/ award-nomination/?ecategory= Awards&rcategory=Awardee Contact: support@aidatascientists.com #worldresearchawards #researchawards #AcademicAwards #ScienceAwards #ArtificialIntelligence  #PhysicsInformedAI #DifferentialEquations #ScientificMachineLearning  

 Matrix Spectral Norm and Optimal Low-Rank Approximation This study examines the spectral norm as a fundamental measure in matrix approximation theory. Using singular value decomposition (SVD), operator norms, and perturbation analysis, we derive conditions for best low-rank approximations under the spectral norm. visit:  aidatascientits.com Nominate:  https://aidatascientists.com/ award-nomination/?ecategory= Awards&rcategory=Awardee Contact:  support@aidatascientists.com #worldresearchawards #researchawards #AcademicAwards #ScienceAwards #ArtificialIntelligence #MatrixTheory #SpectralNorm #SingularValueDecomposition