Satellites based positioning has been widely applied to many areas in our daily lives and thus become indispensable, which also leads increasing demand for high-positioning accuracy. In some complex environments (such as dense urban, valley), multipath interference is one of the main error sources deteriorating accuracy, it difficult eliminate via differential techniques due its uncertainty occ...

Reliable prediction of individual learning performance can facilitate timely support to students and improve the experience. In this study, two well-known machine-learning techniques, that is, vector machine (SVM) artificial neural network (ANN), are hybridized by teaching–learning-based optimizer (TLBO) reliably predict student exam (fail-pass classes final scores). For defined classification ...

The availability of sustainable, efficient electricity access is critical for rural communities as it can facilitate economic development and improve the quality life residents. Isolated microgrids provide a solution electrification, they generate from local renewable energy sources operate independently central grid. Residential load scheduling also an important aspect management in isolated m...

Dynamic economic load dispatch (DELD), which determines the best generation scheduling for different power plants during next 24 hours in order to meet electricity demand as well minimize total energy cost, is a highly complex non-linear and non-convex problem. This study proposes an efficient modified teaching-learning-based optimization algorithm, called MTLBO, effectively solve DELD problem ...

The surface tension (ST) of ionic liquids (ILs) and their accompanying mixtures allows engineers to accurately arrange new processes on the industrial scale. Without any doubt, experimental methods for specification ST every supposable IL its with other compounds would be an arduous job. Also, measurements are effortful prohibitive; thus, a precise estimation property via dependable method grea...

This paper focuses on expanding and evaluating an automatic generation control (AGC) system of a hydrothermal system by modelling the appropriate generation rate constraints to operate practically in an economic manner. The hydro area is considered with an electric governor and the thermal area is modelled with a reheat turbine. Furthermore, the integral controllers and electri...

The teaching–learning-based optimization algorithm (TLBO) is an efficient optimizer. However, it has several shortcomings such as premature convergence and stagnation at local optima. In this paper, the strengthened (STLBO) proposed to enhance basic TLBO’s exploration exploitation properties by introducing three strengthening mechanisms: linear increasing teaching factor, elite system composed ...

This paper presents a new population based parameter free optimization algorithm as teaching learning based optimization (TLBO) and its application to automatic load frequency control (ALFC) of multi-source power system having thermal, hydro and gas power plants. The proposed method is based on the effect of the influence of teacher on the output of learners and the learners can enhance their k...

Abstract As the groundwater quantitative monitoring aimed to determine factors affecting aquifer behavior plays an important role in its regional management, studying temporal and spatial level variations requires a comprehensive network. Effort has been made this study introduce new linked simulation–optimization method, named MLPG-TLBO quantitatively monitor Birjand optimal points for piezome...