We present an approach based on the improved Levenberg Marquardt (LM) algorithm of backpropagation (BP) neural network to estimate the light source position in bioluminescent imaging. For solving the forward problem, the table-based random sampling algorithm (TBRS), a fast Monte Carlo simulation method we developed before, is employed here. Result shows that BP is an effective method to positio...

Scaling models is one of the challenges for water resource planning and management, with aim bringing developed into practice by applying them to predict quality quantity catchments that lack sufficient data. For this study, we evaluated artificial neural network (ANN) training algorithms index in a source catchment. Then, multiple linear regression (MLR) were developed, using predicted ANN var...

Abstract Multi-frequency and multi-component extra-deep azimuthal resistivity measurements with depth of investigation a few tens meters provide advanced possibilities for mapping complex reservoir structures. Inversion the induction set becomes an important technical problem. We present regularized Levenberg–Marquardt algorithm inversion in 2D environment model pixel-based distribution. The co...

Artificial neural networks are applied to model the manoeuvrability characteristics of a ship based on empirical information acquired from experiments with scaled model. This work aims evaluate performance proposed method training artificial network even very small quantity noisy data. The data used for consisted zig-zag and circle manoeuvres carried out in agreement IMO standards. wind effect ...

In this paper we tackle the problem of automatically aligning an unordered set of range views. We propose a full pipeline that goes from the scans to the complete 3D model. The emphasis is on the automation – no manual intervention is require – and on the fact that no knowledge on the acquisition sequence is assumed. The contribution is twofold: in the pre-alignment phase a voting scheme is pro...

A related input parameter is used in this case study to forecast solar thermal systems (STS) capabilities and compare which artificial neural network (ANN) algorithms other intelligence (AI) methods have the most reliable predictor for STS performance. In order gauge performance of STS, research aims implement AI predicting by comparing ANN technique with methods. Three different training are L...

In this study, some physical and mechanical properties of yellow pine wood (Pinus sylvestris), which is used extensively in furniture industry, were tested after heat treatment. The findings obtained modelled by artificial neural network (ANN) interval values related to temperature time variations tried be estimated. This makes it easier reach intermediate values, aims save the relevant researc...

Incorporating higher-order optimization functions, such as Levenberg–Marquardt (LM) have revealed better generalizable solutions for deep learning problems. However, these functions suffer from very large processing time and training complexity especially datasets become large, in multi-view classification problems, where finding global optima is a costly problem. To solve this issue, we develo...