Use of backpropagation and differential evolution algorithms to training MLPs

Artificial Neural Networks (ANNs) are often used (trained) to find a general solution in problems where a pattern needs to be extracted, such as data classification. Feedforward (FFNN) is one of the ANN architectures and multilayer perceptron (MLP) is a type of FFNN. Based on gradient descent, backpropagation (BP) is one of the most used algorithms for MLP training. Evolutionary algorithms can be also used to train MLPs, including Differential Evolution (DE) algorithm. In this paper, BP and DE are used to train MLPs and they are both compared in four different approaches: (a) backpropagation, (b) DE with fixed parameter values, (c) DE with adaptive parameter values and (d) a hybrid alternative using both DE+BP algorithms. © 2013 IEEE

Motoneurone synchronization for intercostal and abdominal muscles: interneurone influences in two different species

The contribution of branched-axon monosynaptic inputs in the generation of short-term synchronization of motoneurones remains uncertain. Here, synchronization was measured for intercostal and abdominal motoneurones supplying the lower thorax and upper abdomen, mostly showing expiratory discharges. Synchronization in the anaesthetized cat, where the motoneurones receive a strong direct descending drive, is compared with that in anaesthetized or decerebrate rats, where the direct descending drive is much weaker. In the cat, some examples could be explained by branched-axon monosynaptic inputs, but many others could not, by virtue of peaks in cross-correlation histograms whose widths (relatively wide) and timing indicated common inputs with more complex linkages, e.g., disynaptic excitatory. In contrast, in the rat, correlations for pairs of internal intercostal nerves were dominated by very narrow peaks, indicative of branched-axon monosynaptic inputs. However, the presence of activity in both inspiration and expiration in many of the nerves allowed additional synchronization measurements between internal and external intercostal nerves. Time courses of synchronization for these often consisted of combinations of peaks and troughs, which have never been previously described for motoneurone synchronization and which we interpret as indicating combinations of inputs, excitation of one group of motoneurones being common with either excitation or inhibition of the other. Significant species differences in the circuits controlling the motoneurones are indicated, but in both cases, the roles of spinal interneurones are emphasised. The results demonstrate the potential of motoneurone synchronization for investigating inhibition and have important general implications for the interpretation of neural connectivity measurements by cross-correlation

Grammatical Evolution for the Multi-Objective Integration and Test Order Problem

Search techniques have been successfully applied for solving different software testing problems. However, choosing, implementing and configuring a search technique can be hard tasks. To reduce efforts spent in such tasks, this paper presents an offline hyper-heuristic named GEMOITO, based on Grammatical Evolution (GE). The goal is to automatically generate a Multi-Objective Evolutionary Algorithm (MOEA) to solve the Integration and Test Order (ITO) problem. The MOEAs are distinguished by components and parameters values, described by a grammar. The proposed hyper-heuristic is compared to conventional MOEAs and to a selection hyper-heuristic used in related work. Results show that GEMOITO can generate MOEAs that are statistically better or equivalent to the compared algorithms

An Approach for the Generation of Multi-Objective Algorithms Applied to the Integration and Test Order Problem

Multi-Objective Evolutionary Algorithms (MOEAs) have been successfully applied to solve hard real software engineering problems. However, to choose and design a MOEA is considered a difficult task, since there are several parameters and components to be configured. These aspects directly impact the generated solutions and the performance of MOEAs. In this sense, this paper proposes an approach for the automatic generation of MOEAs applied to the Integration and Test Order (ITO) problem. Such a problem refers to the generation of optimal sequences of units for integration testing. The approach includes a set of parameters and components of different MOEAs, and is implemented with two design algorithms: Grammatical Evolution (GE) and Iterated Racing (irace). Evaluation results are presented, comparing the MOEAs generated by both design algorithms. Furthermore, the generated MOEAs are compared to two well-known MOEAs used in the literature to solve the ITO problem. Results show that the MOEAs generated with GE and irace perform similarly, and both outperform traditional MOEAs. The approach can reduce efforts spent to design and configure MOEAs, and serves as basis for implementing solutions to other software engineering problems

PENGARUH METODE KESELURUHAN DAN METODE BAGIAN TERHADAP KETERAMPILAN LAY UP SHOOT DALAM PERMAINAN BOLABASKET DI SMK PASUNDAN 1 BANDUNG

ABSTRAK PENGARUH METODE KESELURUHAN DAN METODE BAGIAN TERHADAP KETERAMPILAN LAY UP SHOOT DALAM PERMAINAN BOLABASKET DI SMK PASUNDAN 1 BANDUNG Oleh: Agus Tayudin Skripsi ini dibimbing oleh: Lukmannul Haqim Lubay, M.Pd Skripsi ini membahas mengenai upaya peneliti untuk meningkatkan keterampilan gerak dasar lay up shoot dalam pembelajaran bolabasket melalui penerapan metode bagian dan metode keseluruhan. Skripsi ini merupakan penelitian eksperimen yang pada dasarnya memiliki masalah dalam lay up shoot permainan bolabasket di SMK Pasundan 1 Bandung. Hasil dari tes dan penelitian Kelompok metode bagian memiliki nilai 4,68 sedangkan nilai kelompok metode keseluruhan sebesar 5,38. Dari uji hipotesis hasil tes ini memiliki nilai signifiksasi 0,0001. bahwa hasil dari kedua kelompok ini memiliki perbedaan yang cukup jauh tentunya. berdasarkan output nilai (Sig. (2-tailed) kedua kelompok ini memiliki hasil dari uji hipotesis sebesar 0,0001 dan 0,0001 < 0,05. Dengan demikian H0 ditolak. Maka dari itu kesimpulanya adalah metode keseluruhan dapat memberikan dampak yang signifikan daripada metode bagian terhadap peningkatan keterampilan lay up shoot permainan bolabasket di SMK Pasundan 1 Bandung. Kata Kunci: lay up shoot, metode bagian dan metode keseluruhan, permainan bolabasket

A multi-objective and evolutionary hyper-heuristic applied to the Integration and Test Order Problem

The field of Search-Based Software Engineering (SBSE) has widely utilized Multi-Objective Evolutionary Algorithms (MOEAs) to solve complex software engineering problems. However, the use of such algorithms can be a hard task for the software engineer, mainly due to the significant range of parameter and algorithm choices. To help in this task, the use of Hyper-heuristics is recommended. Hyper-heuristics can select or generate low-level heuristics while optimization algorithms are executed, and thus can be generically applied. Despite their benefits, we find only a few works using hyper-heuristics in the SBSE field. Considering this fact, we describe HITO, a Hyper-heuristic for the Integration and Test Order Problem, to adaptively select search operators while MOEAs are executed using one of the selection methods: Choice Function and Multi-Armed Bandit. The experimental results show that HITO can outperform the traditional MOEAs NSGA-II and MOEA/DD. HITO is also a generic algorithm, since the user does not need to select crossover and mutation operators, nor adjust their parameters

Mission Analysis and Aircraft Sizing of a Hybrid-Electric Regional Aircraft

The purpose of this study was to explore advanced airframe and propulsion technologies for a small regional transport aircraft concept (approximately 50 passengers), with the goal of creating a conceptual design that delivers significant cost and performance advantages over current aircraft in that class. In turn, this could encourage airlines to open up new markets, reestablish service at smaller airports, and increase mobility and connectivity for all passengers. To meet these study goals, hybrid-electric propulsion was analyzed as the primary enabling technology. The advanced regional aircraft is analyzed with four levels of electrification, 0 percent electric with 100 percent conventional, 25 percent electric with 75 percent conventional, 50 percent electric with 50 percent conventional, and 75 percent electric with 25 percent conventional for comparison purposes. Engine models were developed to represent projected future turboprop engine performance with advanced technology and estimates of the engine weights and flowpath dimensions were developed. A low-order multi-disciplinary optimization (MDO) environment was created that could capture the unique features of parallel hybrid-electric aircraft. It is determined that at the size and range of the advanced turboprop: The battery specific energy must be 750 watt-hours per kilogram or greater for the total energy to be less than for a conventional aircraft. A hybrid vehicle would likely not be economically feasible with a battery specific energy of 500 or 750 watt-hours per kilogram based on the higher gross weight, operating empty weight, and energy costs compared to a conventional turboprop. The battery specific energy would need to reach 1000 watt-hours per kilogram by 2030 to make the electrification of its propulsion an economically feasible option. A shorter range and/or an altered propulsion-airframe integration could provide more favorable results