Pages that link to "Item:Q5120073"

The following pages link to Neural network solution of pantograph type differential equations (Q5120073):

Displaying 16 items.

• A unified approach to study the existence and numerical solution of functional differential equation (Q822178) (← links)
• A new implicit high-order six-step singularly P-stable method for the numerical solution of Schrödinger equation (Q830870) (← links)
• Stochastic approach for the solution of multi-pantograph differential equation arising in cell-growth model (Q1643314) (← links)
• Solving ordinary differential equations using an optimization technique based on training improved artificial neural networks (Q2099861) (← links)
• Comparative study of FeedForward and radial basis function neural networks for solving an environmental boundary value problem (Q2104168) (← links)
• Application of discrete mathematical model in edge distortion correction of moving image (Q2135490) (← links)
• New fractional derivative expression of the shifted third-kind Chebyshev polynomials: application to a type of nonlinear fractional pantograph differential equations (Q2138116) (← links)
• Modified differential transform method for solving linear and nonlinear pantograph type of differential and Volterra integro-differential equations with proportional delays (Q2144119) (← links)
• An investigation of approximate solutions for second order ordinary differential equations using sigmoid-weighted neural networks (Q2144766) (← links)
• Stability of numerical solution to pantograph stochastic functional differential equations (Q2152725) (← links)
• The new class of multistep multiderivative hybrid methods for the numerical solution of chemical stiff systems of first order IVPs (Q2201040) (← links)
• Neural network solution of single-delay differential equations (Q2295437) (← links)
• Neural network method for solving fractional diffusion equations (Q2661030) (← links)
• Hermite Functional Link Neural Network for Solving the Van der Pol–Duffing Oscillator Equation (Q5380555) (← links)
• SLeNN-ELM: a shifted Legendre neural network method for fractional delay differential equations based on extreme learning machine (Q6186117) (← links)
• Multi-layer neural networks for data-driven learning of fractional difference equations' stability, periodicity and chaos (Q6198228) (← links)