This study provides a teaching-learning-based optimization (TLBO) path planning method for an autonomous vehicle in cluttered environment, which takes into account smoothness and the possibility of collision with nearby obstacles. The problem is tackled as multiobjective order to plan efficient that allows travel autonomously crowded settings. TLBO algorithm is used find ideal path, goals fin...

This paper is engrossed in the usage of metaheuristic optimization methods named JAYA algorithm and teacher learning based (TLBO) algorithm, which deal with objective function optimal power flow (OPF) problem. TLBO Jaya are parameter-free algorithms, reduce complexity algorithms. The this to real losses maintain voltages tap positions within their limits. IEEE-39 bus system data considered for ...

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 bulk of water pipes experience major degradation and deterioration problems. This research aims at estimating the condition in Shattora Shaker Al-Bahery’s distribution networks, Egypt. developed models involve training Elman neural network (ENN) feed-forward (FFNN) coupled with particle swarm optimization (PSO), genetic algorithms (GA), sine cosine algorithm (SCA), teaching-learning-based (...

– In this article, Teaching-learning opposition based optimization (TLOBO) algorithm based on the natural phenomenon of teaching and learning is applied to design an optimal higher order stable low pass (LP) and high pass (HP) IIR digital filter using different design criterion. The original TeachingLearning Based Optimization (TLBO) algorithm has been remodeled by merging the concept of opposi...

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...

Nowadays advanced machining processes are widely used by manufacturing industries in order to produce high quality precise and very complex products. These advanced machining processes involve large number of input parameters which may affect the cost and quality of the products. Selection of optimum machining parameters in such advanced machining processes is very important to satisfy all the ...

One of the key reasons for performance discrepancy between a building's intended usage and actual operation is Heat Loss, which describes envelope efficiency during in-use circumstances. In this setting, ANN models’ use energy analysis green buildings has become more established. This research aims to anticipate heat loss utilizing two artificial neural network-based methodologies (ANN). partic...

The task of speaker diarization is to answer the question "who spoke when?" In this paper, we present different clustering approaches which consist of Evolutionary Computation Algorithms (ECAs) such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, and Differential Evolution (DE) algorithm as well as Teaching-Learning-Based Optimization (TLBO) technique as a new optimizati...

Seismic isolation systems exposed to far-fault earthquakes can reduce floor accelerations and story drift ratios acceptable levels. However, they exhibit different structural performances in each earthquake due excitation frequency contents. By optimizing the system parameters, their performance may be maintained at best level under earthquakes. In this study, optimization of parameters nonline...