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Function Optimization and Clustering Using Computational Intelligence Techniques

Thesis Info

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Author

Iqbal, M. Amjad

Program

PhD

Institute

National University of Computer and Emerging Sciences

City

Islamabad

Province

Islamabad

Country

Pakistan

Thesis Completing Year

2010

Thesis Completion Status

Completed

Subject

Computer Science

Language

English

Link

http://prr.hec.gov.pk/jspui/handle/123456789/1057

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676727763505

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Function optimization (constrained and unconstrained) is a process of finding the optimal point for the given problem. As the research is being carried out and new problem areas are being investigated, global optimization problems are getting more and more complex. The research presented in this dissertation is about to build a new accelerated function optimization technique based on evolutionary algorithm (EA). EAs have low convergence rate due to their evolutionary nature. The acceleration of evolutionary algorithm in the function optimization is achieved by incorporating gene excitation. In General, the distribution of the initial population into the search space effects the evolutionary algorithm performance. Concept of opposition based populations is employed to distribute the chromosomes more effectively. Image Segmentation is a significant and successful way for many real world applications like segmenting lung from CT scanned images. Segmentation is the process of finding optimal segments within an image. The main objective of this thesis is to make a new entirely automatic system that segments the lungs from the CT scanned images. To achieve this objective, a completely automatic un-supervised scheme is developed to segment lungs. The methodology utilizes a fuzzy histogram based image filtering technique to remove the noise, which preserves the image details for low as well as highly corrupted images. Peaks and Valley are found in bimodal group of images using Genetic Algorithm (GA). GAs are used for function optimization process and hence determining the global optimal solutions. The optimal and dynamic grey level is find out by using GA. Finding optimal clustering within a dataset is an important data mining task. Clustering and segmentations are somewhat related optimization problems of finding optimal grouping in the provided set of points. Clustering of datasets has been achieved by using an entirely automatic un-supervised approach. The employed technique optimizes multi- objective as compared to optimize single objective for clustering. Relative cloning is performed to adopt the individuals according to their fitness, which improves the algorithm performance.
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بابا بلھے شاہ

حضرت بابا بلھے شاہ نے بھٹو کی پیدائش سے کئی سو سال پہلے فرمایا ،جو آج بھی سنہری الفاظ میںیاد کیے جاتے ہیں ۔

ہند تے سندھ دی ونڈ ہوسی

کج حصہ قصور دا جاسی

پتر سندھڑی دا حکمران ہوسی

بنا عدل او ماریا جاسی

 

عرب عہد جاہلیت میں ’’طلاق‘‘ کا تصور: تحقیقی جائزہ

Conjugal life is an important aspect of human society, on which a prosperous life depends. Almost every Culture, civilization and religion Legislate for family life. There is a part of these laws to end the marital relationship which is denoted by "DIVORCE". Divorce is mentioned in detail in Islamic Sharia, in order to understand them truly one has to genuinely consider and understand the concept of divorce in Pre-Islamic period of ignorance. There were several specific terms for divorce that were used in the Arab culture for example Talᾱq, Īela and Khula etc. But generally decent people use the word "طلاق"(Talᾱq) to end the marital relationship. There were some common causes and reasons for divorce in Arabs before Islam for example lack of mental harmony, infertility, bigotry, family feud and apostasy etc. The divorced women become more and more vulnerable socially and economically in ancient Arab and consequently their children less attention, love and affection of their mothers turning them into rebellious, nonconformist and ruthless individuals crossing all limits of oppression and we often see examples of such incidents in Arabs before dawn of Islam. These cruel customs and practices were uprooted through teachings of Islam which is based on justice, equality and basic human rights.

Characterization and Bio-Evaluation of Some Indigenous Legume Protein Isolates for Complementary Foods

In present investigation, extraction, characterization and bio-evaluation of protein isolates from different indigenous legumes i.e. chickpea, lentil, broad and kidney beans were carried out to develop complementary foods. In tested legumes, after inactivation of anti-nutritional factors, protein isolates were prepared through isoelectric precipitation method. The highest protein yield as 80.47±5.71% was estimated in lentil protein isolates (LPI) followed by 73.14±3.44% in chickpea protein isolates (CPI) and 67.58±3.70% in broad bean protein isolates (BPI) while the lowest yield 52.83±3.36% was in kidney bean protein isolates (KPI). Moreover, protein isolates were assessed for their functional properties like bulk density, oil & water absorption, emulsifying & foaming properties etc. Maximum bulk density was revealed in LPI followed by CPI, KPI and BPI. Likewise, higher water absorption capacity was recorded in CPI tracked by LPI and BPI whilst the lowest in KPI. Maximum foaming capacity (FC) was revealed in BPI followed by KPI and LPI, respectively and the minimum in CPI. Electrophorogram through SDS-PAGE showed that legume protein isolates had protein bands in the range of 4 to 70kDa. Amino acid quantification was also performed with reference to requisite profile for the pre-schoolers. Among the essential amino acids, higher lysine content (4.54±0.21g/100g) was found in KPI followed by CPI (3.70±0.09g/100g) and LPI (3.66±0.20g/100g) whilst BPI showed minimum values (3.51±0.21g/100g). Simultaneously, amino acid scores were also determined with values of 39.6, 40.0, 40.0 and 56.0 in CPI, LPI, BPI and KPI, respectively. Bio-evaluation of respective isolates was performed through growth study parameters. Among the resultant protein isolates, the highest values were observed in LPI followed by CPI and BPI while the lowest for KPI regarding protein efficiency ratio (PER), net protein (NPR) and relative net protein ratio (RNPR), respectively for the year 2009-10. Similarly, nitrogen balance study parameters showed the highest values for true digestibility (TD), biological value (BV) & net protein utilization (NPU) in LPI tracked by CPI and BPI whereas the lowest values for these traits were recorded in KPI. However, BV value was high in KPI as compared to BPI. Similar trend for growth and nitrogen balance studies was observed in the next year 2010- 11. On the basis of overall yield, functional properties and bio-evaluation, two best protein isolates namely LPI and CPI were selected along with control for complementary foods preparation. The prepared formulations based on LPI (C1) and CPI (C2) congregated the FAO criteria for supplementary infant foods. The developed weaning foods were analyzed for chemical composition, energy value, bulk density, reconstitution index, viscosity and amino acid profile. Additionally, gross calorific values were observed as 401.70±20.42, 401.15±20.50 and 410.16±20.90kcal/100g for C1, C2 and control complementary foods, respectively. The essential amino acids were found to be sufficient in lentil and chickpea protein supplemented weaning foods. In addition to amino acid quantification for infant formulations, amino acid scores were also estimated. In complementary foods, maximum calorific value was contributed by fat followed by protein. Formulations in current study are capable of delivering 120.22±6.80, 122.49±6.36 and 123.27±6.09kcal per single meal for C1, C2 and control, respectively. Hedonic response regarding various sensory attributes also showed acceptance towards developed complementary foods. The acceptability appraisal of prepared infant formulations was conducted through short term infant feeding trial with the help of nursing mothers. The acceptability remained as 61.40 to 65.00% at the initiation of study and reached to 80.80 to 83.20% at the end of trial. Correlation studies also showed strong association among various variables and refelect their positive and negative contributions. The upshots of this project indicated that indigenous legumes have potential to yield protein isolates with appreciable functional and nutritional quality for application in array of foods with special reference to complementary foods.