Step-Optimized Particle Swarm Optimization

Particle swarm optimization (PSO) is widely used in industrial and academic research to solve optimization problems. Recent developments of PSO show a direction towards adaptive PSO (APSO). APSO changes its behaviour during the optimization process based on information gathered at each iteration. It has been shown that APSO is able to solve a wide range of difficult optimization problems efficiently and effectively. In classical PSO, all parameters are fixed for the entire swarm. In particular, all particles share the same settings of their velocity weights. We propose four APSO variants in which every particle has its own velocity weights. We use PSO to optimize the settings of the velocity weights of every particle at every iteration, thereby creating a step-optimized PSO (SOPSO). We implement four known PSO variants (global best PSO, decreasing weight PSO, time-varying acceleration coefficients PSO, and guaranteed convergence PSO) and four proposed APSO variants (SOPSO, moving bounds SOPSO, repulsive SOPSO, and moving bound repulsive SOPSO) in a PSO software package. The PSO software package is used to compare the performance of the PSO and APSO variants on 22 benchmark problems. Test results show that the proposed APSO variants outperform the known PSO variants on difficult optimization problems that require large numbers of function evaluations for their solution. This suggests that the SOPSO strategy of optimizing the settings of the velocity weights of every particle improves the robustness and performance of PSO

KLASIFIKASI SEKOLAH SLTP BANJARMASIN BERBASIS TIK BERDASARKAN SARANA DAN PRASARANA MENGGUNAKAN K-NEAREST NEIGHBOR BERBASIS PARTICLE SWARM OPTIMIZATION

Dua faktor yang dapat menjelaskan mengapa upaya perbaikan mutu pendidikan selama ini kurang atau tidak berhasil. Pertama sifat pembangunan selama ini lebih bersifat input oriented. Strategi yang demikian lebih bersandar kepada asumsi bahwa bilamana semua input pendidikan telah terpenuhi seperti penyediaan sarana prasarana berbasis TIK, pelatihan guru dan tenaga kependidikan lainnya, maka secara otomatis lembaga pendidikan (sekolah) akan menghasilkan output (keluaran) yang bermutu sebagaimana yang diharapkan.  Standar kompetensi berbasis TIK di klasifikasikan dalam label non berbatik, perintis, menengah dan lanjut, dalam pengambilan keputusan tersebut memerlukan waktu yang lama untuk menganalisa dalam mengklasifikasi sekolah berbasis TIK sehingga hasilnya menjadi kurang akurat, dari permasalahan yang ada tersebut digunakan metode klasifikasi pada data mining yang dapat mengklasifikasi SLTP berbasis TIK. Dalam penelitian ini diterapkan algoritma yang cukup baik dalam mengklasifikasi SLTP berbasis TIK yaitu metode K-Nearest Neighbor (KNN) dan Particle Swarm Optimization (PSO) yang digunakan untuk menghitung bobot setiap attributnya. Dari hasil pengujian dengan model tersebut maka hasil yang didapat algoritma KNN saja sudah menghasilkan akurasi sebesar 90% dan klasifikasi error sebesar 10% kemudian setelah dilakukan pembobotan berbasis PSO nilai akurasinya meningkat menjadi 97.14% dan klasifikasi error turun menjadi 2.86%. Hasil klasifikasi target perintis lebih banyak dari pada non berbatik, menengah dan lanjut, dengan adanya peningkatan tersebut model yang diperoleh pun menjadi lebih akurat dalam mengklasifikasi SLTP berbasis TIK.Kata kunci : Data Mining, Algoritma K-Nearest Neighbor, Particle Swarm Optimizatio

Localized Spot Patterns for the Brusselator Reaction-Diffusion System

The Brusselator reaction-diffusion model characterizes dynamical processes of some reaction diffusion systems in chemistry, physics, biology, and geology. On the sphere, the solutions of the Brusselator system center on a discrete set of points. In this thesis, we study the system of differential-algebraic equations (DAEs) that describes the slow dynamics of localized spot patterns for the Brusselator model on the surface of a unit sphere. The DAE system is solved numerically using Matlab's ode15s function. The relationship between the equilibria of the DAE system and the set of elliptic Fekete points is studied. Precisely, solutions of DAE system are obtained from solving the elliptic Fekete optimization problem. The optimization problem is solved using the particle swarm optimization method. It is verified that for N=2,3,...,8 spots, the equilibrium spot configurations of the DAE system starting from a set of random initial points are elliptic Fekete points

Klasifikasi Kelas Risiko Paien Pneumonia Menggunakan Metode Hybrid Analisis Diskriminan Linier-Particle Swarm Optimization (ADL-PSO) dan Naive Bayes Classification

sehingga penyebaran penyakit ini tergolong sangat cepat. Oleh karena itu diagnosa yang cepat dan tepat sangat diperlukan agar dapat menentukan penanganan dan perawatan yang tepat. Beberapa penilaian kelas risiko pneumonia dikembangkan untuk mempermudah diagnosis pneumonia. Terdapat berbagai sistem skoring PSI, CURB-65, modified ATS (m-ATS) dan sebagainya untuk menentukan kelas risiko pasien pneumonia, akan tetapi tidak ada patokan pasti untuk menentukan sistem apa yang harus digunakan untuk mengelompokan kelas risiko pneumonia. Oleh karena itu diperlukan studi klasifikasi untuk mengkaji variabel-variabel yang diapat digunakan untuk mengelompokan kelas risiko pneumonia secara tepat. Penelitian ini menerapkan metode Analisis Diskriminan Linier dengan seleksi variabel forward selection, backward elimination dan stepwise method, Hybrid Analisis Diskriminan Linier-Particle Swarm Optimization (ADL-PSO) dan Naïve Bayes untuk mengklasifikasikan kelompok kelas risiko pneumonia berdasarkan data rekam medis pasien kemudian ketiga metode klasifikasi tersebut dibandingkan nilai akurasinya. Hasil penelitian menunjukan bahwa metode klasifikasi terbaik adalah ADL-PSO. ========================================================================================= Pneuomonia is a disease that is transmitted through the air so that the spread of this disease is very fast. Therefore a fast and precise diagnosis is necessary in order to determine appropriate treatment and care. Several scoring assessments of pneumonia were developed to facilitate the diagnosis of pneumonia. There are PSI scoring systems, CURB-65, modified ATS (m-ATS) and so on to determine the risk class of pneumonia patients, but there is no definite benchmark to determine what system should be used to classify the risk class of pneumonia. Therefore, a classification study is needed to assess the variables used to correctly classify the risk of pneumonia. This research applies Linear Discriminant Analysis method with selection of forward selection, backward elimination and stepwise method, Hybrid Linear Discriminant Analysis-Particle Swarm Optimization (LDA-PSO) and Naïve Bayes to classify pneumonia risk class group based on patient medical record data then all classification methods are compared the value of its accuracy. The results showed that the best classification method is LDA-PSO

Characterization of edge-contact influence on tridimensional elastohydrodynamic film shape, pressure, stress and temperature distributions

This doctoral project investigates edge contact influence on pressure, lubricant film thickness, temperature, and stress distribution of finite line contacts under an elastohydrodynamic lubrication (EHL) regime. This type of contact represents a common source of problems in engineering structures such as gears, cams and roller bearings, since non-conforming contact surfaces in such structures undergo intense stresses while transferring loads through relatively small contact areas. Additionally, they induce stressconcentration zones at their extremities; as a result, profile modification becomes necessary. The present study investigates influence of free edges on EHL characteristics of finite line contacts. The initial stage of the research develops a 3D numerical model for the thermal, non-Newtonian EHL of general contact problems. A semi-analytical method (SAM), based on the Boussinesq half-space theory, is combined with a free boundary correction process to provide a fast and precise description of edge contact conditions. A modified finite difference expansion of the Couette term of the Reynolds equation guarantees computational stability, while the Carreau expression defines the shear-thinning response of the lubricant. Free boundary impact on tridimensional stress distribution is also investigated by extending the free-edge correction procedure to evaluate the levels of surface and subsurface stresses using SAM. The stress distribution data derived from this procedure are then contrasted with Finite Element Method (FEM) results using a two-level factorial comparison. Three dimensionless factors — contact slenderness, contact length ratio, and load — are examined. The comparison shows that the new model developed in this thesis provides a high level of precision in the evaluation of stress distributions, while computing more than 125 times faster than FEM simulations. This powerful model is then used to investigate and establish the influence of different roller profile modifications on EHL film shape, pressure and temperature distributions. Based on a series of detailed analyses of different roller profile corrections, it is found that a large radius crowning combined with rounding corners provides the most effective profile adjustment. In the last step of this study, this newly developed model is combined with a multi-objective particle swarm optimization (PSO) to arrive at formulas establishing crowning and corner rounding radii, which can be applied to the rapid design of optimal rollers. The formulas take into account three dimensionless factors — slenderness, load, and lubricant viscosity — and coefficients for the formulas are derived from the PSO results using a five-level factorial design. By concurrently optimizing three objective functions — contact pressure uniformity, film thickness stability, and maximum load capacity — the predictions of these formulas guarantee optimal profile modifications. This study contributes to the understanding of edge influence on EHL characteristics of finite line contacts, while offering a robust model for axial profile corrections of lubricated contact problems

Systematic construction of efficient six-stage fifth-order explicit Runge-Kutta embedded pairs without standard simplifying assumptions

This thesis examines methodologies and software to construct explicit Runge-Kutta (ERK) pairs for solving initial value problems (IVPs) by constructing efficient six-stage fifth-order ERK pairs without standard simplifying assumptions. The problem of whether efficient higher-order ERK pairs can be constructed algebraically without the standard simplifying assumptions dates back to at least the 1960s, with Cassity's complete solution of the six-stage fifth-order order conditions. Although RK methods based on the six-stage fifth-order order conditions have been widely studied and have continuing practical importance, prior to this thesis, the aforementioned complete solution to these order conditions has no published usage beyond the original series of publications by Cassity in the 1960s. The complete solution of six-stage fifth-order ERK order conditions published by Cassity in 1969 is not in a formulation that can easily be used for practical purposes, such as a software implementation. However, it is shown in this thesis that when the order conditions are solved and formulated appropriately using a computer algebra system (CAS), the generated code can be used for practical purposes and the complete solution is readily extended to ERK pairs. The condensed matrix form of the order conditions introduced by Cassity in 1969 is shown to be an ideal methodology, which probably has wider applicability, for solving order conditions using a CAS. The software package OCSage developed for this thesis, in order to solve the order conditions and study the properties of the resulting methods, is built on top of the Sage CAS. However, in order to effectively determine that the constructed ERK pairs without standard simplifying assumptions are in fact efficient by some well-defined criteria, the process of selecting the coefficients of ERK pairs is re-examined in conjunction with a sufficient amount of performance data. The pythODE software package developed for this thesis is used to generate a large amount of performance data from a large selection of candidate ERK pairs found using OCSage. In particular, it is shown that there is unlikely to be a well-defined methodology for selecting optimal pairs for general-purpose use, other than avoiding poor choices of certain properties and ensuring the error coefficients are as small as possible. However, for IVPs from celestial mechanics, there are obvious optimal pairs that have specific values of a small subset of the principal error coefficients (PECs). Statements seen in the literature that the best that can be done is treating all PECs equally do not necessarily apply to at least some broad classes of IVPs. By choosing ERK pairs based on specific values of individual PECs, not only are ERK pairs that are 20-30% more efficient than comparable published pairs found for test sets of IVPs from celestial mechanics, but the variation in performance between the best and worst ERK pairs that otherwise would seem to have similar properties is reduced from a factor of 2 down to as low as 15%. Based on observations of the small number of IVPs of other classes in common IVP test sets, there are other classes of IVPs that have different optimal values of the PECs. A more general contribution of this thesis is that it specifically demonstrates how specialized software tools and a larger amount of performance data than is typical can support novel empirical insights into numerical methods