Pub Date : 2015-02-01DOI: 10.1504/IJAISC.2015.067525
S. Iram, P. Fergus, D. Al-Jumeily, A. Hussain, M. Randles
People in developed countries are living longer, and this has resulted in the prevalence of age-related diseases like Alzheimer's and dementia. Many believe that the early detection of neurodegenerative diseases will provide a much more sustainable framework for dealing with age-related diseases in the future. This paper considers this idea and proposes a new classifier fusion strategy that combines classification algorithms and rules voting, product, mean, median, maximum and minimum to measure specific behaviours in people suffering with neurodegenerative diseases. More specifically, the fusion strategy analyses the stride-to-stride intervals in gait and its correlation with neurological functions. This approach is compared with base level classifiers a single classification algorithm using a set of feature vectors associated with gait patterns obtained from neurodegenerative patients and healthy people. The results show that the fusion strategy improves classification. Our experiments successfully show that a fusion strategy generates better results and classifies subjects more accurately than base level classifiers.
{"title":"A classifier fusion strategy to improve the early detection of neurodegenerative diseases","authors":"S. Iram, P. Fergus, D. Al-Jumeily, A. Hussain, M. Randles","doi":"10.1504/IJAISC.2015.067525","DOIUrl":"https://doi.org/10.1504/IJAISC.2015.067525","url":null,"abstract":"People in developed countries are living longer, and this has resulted in the prevalence of age-related diseases like Alzheimer's and dementia. Many believe that the early detection of neurodegenerative diseases will provide a much more sustainable framework for dealing with age-related diseases in the future. This paper considers this idea and proposes a new classifier fusion strategy that combines classification algorithms and rules voting, product, mean, median, maximum and minimum to measure specific behaviours in people suffering with neurodegenerative diseases. More specifically, the fusion strategy analyses the stride-to-stride intervals in gait and its correlation with neurological functions. This approach is compared with base level classifiers a single classification algorithm using a set of feature vectors associated with gait patterns obtained from neurodegenerative patients and healthy people. The results show that the fusion strategy improves classification. Our experiments successfully show that a fusion strategy generates better results and classifies subjects more accurately than base level classifiers.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125337547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-02-01DOI: 10.1504/IJAISC.2015.067526
Neil Morgan, Mohammed Saeed
This research project investigated the issues and opportunities associated with making digital mapping and spatial data more accessible and usable for the blind. Geographical information systems GIS enable the storage and manipulation of raster and vector data based upon the spatial relationships of individual features. While GIS predominantly rely on the visual medium for the presentation of data, the ability to store and manipulate spatial relationships offers opportunities to present data using alternative modalities such as speech, sound and haptic feedback. A group of eight blind participants took part in a task driven experiment using two interface designs. The effectiveness of each interface design was assessed through task performance and user experience questionnaires. The results obtained suggest that interface design, data presentation and the use of multiple modalities has the potential to enhance accessibility, usability and support spatial cognition.
{"title":"A comparative study of multimodal digital map interface designs for blind users","authors":"Neil Morgan, Mohammed Saeed","doi":"10.1504/IJAISC.2015.067526","DOIUrl":"https://doi.org/10.1504/IJAISC.2015.067526","url":null,"abstract":"This research project investigated the issues and opportunities associated with making digital mapping and spatial data more accessible and usable for the blind. Geographical information systems GIS enable the storage and manipulation of raster and vector data based upon the spatial relationships of individual features. While GIS predominantly rely on the visual medium for the presentation of data, the ability to store and manipulate spatial relationships offers opportunities to present data using alternative modalities such as speech, sound and haptic feedback. A group of eight blind participants took part in a task driven experiment using two interface designs. The effectiveness of each interface design was assessed through task performance and user experience questionnaires. The results obtained suggest that interface design, data presentation and the use of multiple modalities has the potential to enhance accessibility, usability and support spatial cognition.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134564021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-02-01DOI: 10.1504/IJAISC.2015.067523
H. Alaskar, D. Lamb, A. Hussain, D. Al-Jumeily, M. Randles, P. Fergus
This paper investigates a set of approaches for the prediction of noisy time series data; specifically, the prediction of financial signals. A novel dynamic self-organised multilayer neural network based on the immune algorithm for financial time series prediction is presented, combining the properties of both recurrent and self-organised neural networks. In an attempt to overcome inherent stability and convergence problems, the network is derived to ensure that it reaches a unique equilibrium state. The accuracy of the comparative evaluation is enhanced in terms of profit earning; empirical testing used in this work includes normalised mean square error NMSE to evaluate forecast fitness and also evaluates predictions against financial metrics to assess profit generation. Extensive simulations for multi-step prediction in stationary and non-stationary time series were performed. The resulting forecast made by the proposed network shows substantial profits on financial historical signals when compared to various solely neural network approaches. These simulations suggest that dynamic immunology-based self-organised neural networks have a better ability to capture the chaotic movement in financial signals.
{"title":"Predicting financial time series data using artificial immune system-inspired neural networks","authors":"H. Alaskar, D. Lamb, A. Hussain, D. Al-Jumeily, M. Randles, P. Fergus","doi":"10.1504/IJAISC.2015.067523","DOIUrl":"https://doi.org/10.1504/IJAISC.2015.067523","url":null,"abstract":"This paper investigates a set of approaches for the prediction of noisy time series data; specifically, the prediction of financial signals. A novel dynamic self-organised multilayer neural network based on the immune algorithm for financial time series prediction is presented, combining the properties of both recurrent and self-organised neural networks. In an attempt to overcome inherent stability and convergence problems, the network is derived to ensure that it reaches a unique equilibrium state. The accuracy of the comparative evaluation is enhanced in terms of profit earning; empirical testing used in this work includes normalised mean square error NMSE to evaluate forecast fitness and also evaluates predictions against financial metrics to assess profit generation. Extensive simulations for multi-step prediction in stationary and non-stationary time series were performed. The resulting forecast made by the proposed network shows substantial profits on financial historical signals when compared to various solely neural network approaches. These simulations suggest that dynamic immunology-based self-organised neural networks have a better ability to capture the chaotic movement in financial signals.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131300606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-11-01DOI: 10.1504/IJAISC.2014.065799
B. Datta, Susanta Mitra, S. Pal
In this study, we demonstrate how connectionist models, in particular, multilayer perceptron network can be used for prediction of rainfall. Here we give a comparative study between conventional approach (using multivariate linear regression) and soft computing approach using artificial neural network (ANN). The basic idea is to identify a computational model to characterise the relation between the average monthly rainfalls of a region with that of different neighbouring regions. The model exploits both spatial as well as temporal information to achieve better prediction. Once the computational model is obtained, it is used to predict the average monthly rainfall. Early prediction of rainfall is expected to play a key role in economic planning.
{"title":"Estimation of average monthly rainfall with neighbourhood values: comparative study between soft computing and statistical approach","authors":"B. Datta, Susanta Mitra, S. Pal","doi":"10.1504/IJAISC.2014.065799","DOIUrl":"https://doi.org/10.1504/IJAISC.2014.065799","url":null,"abstract":"In this study, we demonstrate how connectionist models, in particular, multilayer perceptron network can be used for prediction of rainfall. Here we give a comparative study between conventional approach (using multivariate linear regression) and soft computing approach using artificial neural network (ANN). The basic idea is to identify a computational model to characterise the relation between the average monthly rainfalls of a region with that of different neighbouring regions. The model exploits both spatial as well as temporal information to achieve better prediction. Once the computational model is obtained, it is used to predict the average monthly rainfall. Early prediction of rainfall is expected to play a key role in economic planning.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133104753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-11-01DOI: 10.1504/IJAISC.2014.065802
P. Das, F. Pettersson, Shubhabrata Dutta
In this paper, an attempt has been made in this study to grow the concept of modularity along with pruned networks for strength-ductility balance of high strength low alloy (HSLA) steel plates using lower and upperlayer pruning algorithms. Modelling of strength-ductility balance in case of high strength low alloy steel is a major concern in industrial research. In most cases, the cause of inferior mechanical properties of such steel products could not be clearly identified. The comparative analysis with standard fully-connected network and pruned network reveals an improved performance for pruned-modular architecture and explains the metallurgical phenomenon of HSLA steel in a better way.
{"title":"Pruned-bimodular neural networks for modelling of strength-ductility balance of HSLA steel plates","authors":"P. Das, F. Pettersson, Shubhabrata Dutta","doi":"10.1504/IJAISC.2014.065802","DOIUrl":"https://doi.org/10.1504/IJAISC.2014.065802","url":null,"abstract":"In this paper, an attempt has been made in this study to grow the concept of modularity along with pruned networks for strength-ductility balance of high strength low alloy (HSLA) steel plates using lower and upperlayer pruning algorithms. Modelling of strength-ductility balance in case of high strength low alloy steel is a major concern in industrial research. In most cases, the cause of inferior mechanical properties of such steel products could not be clearly identified. The comparative analysis with standard fully-connected network and pruned network reveals an improved performance for pruned-modular architecture and explains the metallurgical phenomenon of HSLA steel in a better way.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"445 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123232507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-11-01DOI: 10.1504/IJAISC.2014.065800
Amita Jain, D. K. Lobiyal
Word sense disambiguation (WSD) is an important task in computational linguistics as it is essential for many language understanding applications. In this paper, we propose a graph-based unsupervised WSD method for Hindi text which disambiguates multiple ambiguous words present in the sentence simultaneously. In our approach, we first construct the semantic graph for each interpretation of the given sentence by establishing semantic relations between the pair of words present in the sentence. We use Hindi WordNet to establish semantic relations between the pair of words and then we construct the graph. We find the cost of spanning tree corresponding to each semantic graph and the interpretation for which spanning tree has the minimum cost is identified. This interpretation is considered as the resulting interpretation. Our approach also considers all open class words unlike the previous approaches which focus only on noun.
{"title":"A new approach for unsupervised word sense disambiguation in Hindi language using graph connectivity measures","authors":"Amita Jain, D. K. Lobiyal","doi":"10.1504/IJAISC.2014.065800","DOIUrl":"https://doi.org/10.1504/IJAISC.2014.065800","url":null,"abstract":"Word sense disambiguation (WSD) is an important task in computational linguistics as it is essential for many language understanding applications. In this paper, we propose a graph-based unsupervised WSD method for Hindi text which disambiguates multiple ambiguous words present in the sentence simultaneously. In our approach, we first construct the semantic graph for each interpretation of the given sentence by establishing semantic relations between the pair of words present in the sentence. We use Hindi WordNet to establish semantic relations between the pair of words and then we construct the graph. We find the cost of spanning tree corresponding to each semantic graph and the interpretation for which spanning tree has the minimum cost is identified. This interpretation is considered as the resulting interpretation. Our approach also considers all open class words unlike the previous approaches which focus only on noun.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121972293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-11-01DOI: 10.1504/IJAISC.2014.065801
Jie Du, H. Wimmer, R. Rada
The purpose of this paper is to examine the role of domain knowledge in guiding evolution. The hypothesis examined in this paper is that the use of knowledge represented as a semantic network will bias mutation so that changes in structure measured by the semantic net correspond to changes in function. This hypothesis is tested utilising information and data from the finance domain. In this paper relevant literature is reviewed and an experimental framework is proposed which incorporates knowledge in evolution. An empirical investigation is presented to demonstrate the role of knowledge and gradualness in evolution. Future work will involve investigating methods to identify or construct a semantic network which is 'meaningful' to humans as well as machines.
{"title":"Knowledge constrained evolutionary algorithms: a case study for financial investing","authors":"Jie Du, H. Wimmer, R. Rada","doi":"10.1504/IJAISC.2014.065801","DOIUrl":"https://doi.org/10.1504/IJAISC.2014.065801","url":null,"abstract":"The purpose of this paper is to examine the role of domain knowledge in guiding evolution. The hypothesis examined in this paper is that the use of knowledge represented as a semantic network will bias mutation so that changes in structure measured by the semantic net correspond to changes in function. This hypothesis is tested utilising information and data from the finance domain. In this paper relevant literature is reviewed and an experimental framework is proposed which incorporates knowledge in evolution. An empirical investigation is presented to demonstrate the role of knowledge and gradualness in evolution. Future work will involve investigating methods to identify or construct a semantic network which is 'meaningful' to humans as well as machines.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133177747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-11-01DOI: 10.1504/IJAISC.2014.065798
Rohit Katiyar, V. Pathak, K. V. Arya
In present scenario biometrics system are getting popular day by day and they are classified based on subject's cooperation and non-cooperation nature. Gait biometrics is one of the popularly traits used for person identification. The gait biometrics has an edge over the other biometrics traits as it works well even if the subject is not cooperative. The multiple problems such as shadow detection, removal of moving subjects in visual surveillance, less number of gallery probes in different conditions and existence of multiple views in the data are encountered due to surveillance camera and affect the performance of the gait recognition system. In this paper, we used three algorithms to overcome these problems up to an extent. In first algorithm, photometric properties based method is used to remove shadows at the time of silhouette generation from the recorded video. Then, an algorithm for synthetic gait energy image (GEI) templates generation employed to increase the corresponding gallery probes dataset and finally, singular value decomposition transformation is applied to transform the gait feature from one view to another. The performance of the proposed algorithm is experimentally validated on a benchmark dataset of indoor as well as outdoor video sequences by comparing it with the existing algorithms.
{"title":"Human gait recognition system based on shadow free silhouettes using truncated singular value decomposition transformation model","authors":"Rohit Katiyar, V. Pathak, K. V. Arya","doi":"10.1504/IJAISC.2014.065798","DOIUrl":"https://doi.org/10.1504/IJAISC.2014.065798","url":null,"abstract":"In present scenario biometrics system are getting popular day by day and they are classified based on subject's cooperation and non-cooperation nature. Gait biometrics is one of the popularly traits used for person identification. The gait biometrics has an edge over the other biometrics traits as it works well even if the subject is not cooperative. The multiple problems such as shadow detection, removal of moving subjects in visual surveillance, less number of gallery probes in different conditions and existence of multiple views in the data are encountered due to surveillance camera and affect the performance of the gait recognition system. In this paper, we used three algorithms to overcome these problems up to an extent. In first algorithm, photometric properties based method is used to remove shadows at the time of silhouette generation from the recorded video. Then, an algorithm for synthetic gait energy image (GEI) templates generation employed to increase the corresponding gallery probes dataset and finally, singular value decomposition transformation is applied to transform the gait feature from one view to another. The performance of the proposed algorithm is experimentally validated on a benchmark dataset of indoor as well as outdoor video sequences by comparing it with the existing algorithms.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"113 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133488544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-01DOI: 10.1504/IJAISC.2014.062825
V. Aakanksha, Ravish Sharma, Punam Bedi
This paper presents an ant-based trusted routing algorithm with load-balancing for mobile ad hoc networks within the framework of mobile process groups MPGs. The proposed algorithm uses a hybrid approach as it proactively forms the group views of mobile processes agents in initialisation phase and maintains and updates these group views reactively in accordance with the topology change in maintenance phase. Route is discovered reactively on-demand when a source node sends a route request for routing. Reactive path setup is instigated by sending ant packets on the trusted paths. These ant packets update the routing path with a pheromone value which is computed using trust on that node and the node's load taking capability. Therefore, ant packets always follow the path which is most trustworthy and has low traffic load density. The proposed approach was implemented in JADE and the results show that the nodes having high trust and less traffic load density were always chosen as forwarding nodes forming the trusted path with less load.
{"title":"Trusted and load-balanced ant-based routing in mobile ad hoc networks","authors":"V. Aakanksha, Ravish Sharma, Punam Bedi","doi":"10.1504/IJAISC.2014.062825","DOIUrl":"https://doi.org/10.1504/IJAISC.2014.062825","url":null,"abstract":"This paper presents an ant-based trusted routing algorithm with load-balancing for mobile ad hoc networks within the framework of mobile process groups MPGs. The proposed algorithm uses a hybrid approach as it proactively forms the group views of mobile processes agents in initialisation phase and maintains and updates these group views reactively in accordance with the topology change in maintenance phase. Route is discovered reactively on-demand when a source node sends a route request for routing. Reactive path setup is instigated by sending ant packets on the trusted paths. These ant packets update the routing path with a pheromone value which is computed using trust on that node and the node's load taking capability. Therefore, ant packets always follow the path which is most trustworthy and has low traffic load density. The proposed approach was implemented in JADE and the results show that the nodes having high trust and less traffic load density were always chosen as forwarding nodes forming the trusted path with less load.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128504108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-01DOI: 10.1504/IJAISC.2014.062815
S. Bali, P. Jha, U. Kumar, H. Pham
During the last two decades, there has been a growing interest in component-based software engineering CBSE both in academia and industry. In component-based system development, it is common to identify software modules first. Once they are identified, we need to select appropriate software components for each module. These components can either be bought as commercial off-the-shelf COTS components and probably adapted to work in the software system or can be developed in-house. This is a 'build-or-buy' decision. This paper discusses a framework that helps a developer to decide whether to buy or to build software components while designing a fault-tolerant modular software system. This paper proposes optimisation models for optimal component selection for a fault-tolerant modular software system under the consensus recovery block scheme. It is necessary to identify critical modules in the design of a fault-tolerant modular software system and also to develop a system with a built in redundancy for critical modules. Therefore, the first optimisation model is developed for optimal component selection with the dual objective of reliability maximisation and cost minimisation of the overall system under the constraints on the delivery time and criticality of modules. The second optimisation model is an extension of the first optimisation model and discusses the issue of compatibility of components of modules. In practice, it is not possible for management to obtain precise value of reliability, cost, delivery time, etc., therefore both the models are formulated as fuzzy multi-objective optimisation models. A case study of developing a manufacturing system for medium-size enterprise is used to illustrate the proposed methodology.
{"title":"Fuzzy multi-objective build-or-buy approach for component selection of fault tolerant software system under consensus recovery block scheme with mandatory redundancy in critical modules","authors":"S. Bali, P. Jha, U. Kumar, H. Pham","doi":"10.1504/IJAISC.2014.062815","DOIUrl":"https://doi.org/10.1504/IJAISC.2014.062815","url":null,"abstract":"During the last two decades, there has been a growing interest in component-based software engineering CBSE both in academia and industry. In component-based system development, it is common to identify software modules first. Once they are identified, we need to select appropriate software components for each module. These components can either be bought as commercial off-the-shelf COTS components and probably adapted to work in the software system or can be developed in-house. This is a 'build-or-buy' decision. This paper discusses a framework that helps a developer to decide whether to buy or to build software components while designing a fault-tolerant modular software system. This paper proposes optimisation models for optimal component selection for a fault-tolerant modular software system under the consensus recovery block scheme. It is necessary to identify critical modules in the design of a fault-tolerant modular software system and also to develop a system with a built in redundancy for critical modules. Therefore, the first optimisation model is developed for optimal component selection with the dual objective of reliability maximisation and cost minimisation of the overall system under the constraints on the delivery time and criticality of modules. The second optimisation model is an extension of the first optimisation model and discusses the issue of compatibility of components of modules. In practice, it is not possible for management to obtain precise value of reliability, cost, delivery time, etc., therefore both the models are formulated as fuzzy multi-objective optimisation models. A case study of developing a manufacturing system for medium-size enterprise is used to illustrate the proposed methodology.","PeriodicalId":364571,"journal":{"name":"Int. J. Artif. Intell. Soft Comput.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133893400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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