Tribological behaviour of aluminium alloy (Al-Si10Mg) reinforced with alumina (9%) and graphite (3%) fabricated by stir casting process was investigated. The wear and frictional properties of the hybrid metal matrix c...Tribological behaviour of aluminium alloy (Al-Si10Mg) reinforced with alumina (9%) and graphite (3%) fabricated by stir casting process was investigated. The wear and frictional properties of the hybrid metal matrix composites was studied by performing dry sliding wear test using a pin-on-disc wear tester. Experiments were conducted based on the plan of experiments generated through Taguchi’s technique. A L27 Orthogonal array was selected for analysis of the data. Investigation to find the influence of applied load, sliding speed and sliding distance on wear rate, as well as the coefficient of friction during wearing process was carried out using ANOVA and regression equations for each response were developed. Objective of the model was chosen as ‘smaller the better’ characteristics to analyse the dry sliding wear resistance. Results show that sliding distance has the highest influence followed by load and sliding speed. Finally, confirmation tests were carried out to verify the experimental results and Scanning Electron Microscopic studies were done on the wear surfaces.展开更多
In this investigation, an approach using Coac-tive Neuro-Fuzzy Inference System (CANFIS) as diagnosis system for breast cancer has been proposed on Wisconsin Breast Cancer Data (WBCD). It is occasionally difficult to ...In this investigation, an approach using Coac-tive Neuro-Fuzzy Inference System (CANFIS) as diagnosis system for breast cancer has been proposed on Wisconsin Breast Cancer Data (WBCD). It is occasionally difficult to attain the ultimate diagnosis even for medical experts due to the complexity and non-linearity of the rela-tionships between the large measured factors, which can be possibly resolved with a human like decision-making process using Artificial Intelligence (AI) algorithms. CANFIS is an AI algorithm which has the advantages of both fuzzy inference system and neural networks and can deal with ambiguous data and learn from the past data by itself. The Multi Layer Percep-tron Neural Network (MLPNN), Probabilistic Neural Network (PNN) Principal Component Analysis (PCA), Support Vector Machine (SVM) and Self Organizing Map (SOM) were also tested and benchmarked for their展开更多
文摘Tribological behaviour of aluminium alloy (Al-Si10Mg) reinforced with alumina (9%) and graphite (3%) fabricated by stir casting process was investigated. The wear and frictional properties of the hybrid metal matrix composites was studied by performing dry sliding wear test using a pin-on-disc wear tester. Experiments were conducted based on the plan of experiments generated through Taguchi’s technique. A L27 Orthogonal array was selected for analysis of the data. Investigation to find the influence of applied load, sliding speed and sliding distance on wear rate, as well as the coefficient of friction during wearing process was carried out using ANOVA and regression equations for each response were developed. Objective of the model was chosen as ‘smaller the better’ characteristics to analyse the dry sliding wear resistance. Results show that sliding distance has the highest influence followed by load and sliding speed. Finally, confirmation tests were carried out to verify the experimental results and Scanning Electron Microscopic studies were done on the wear surfaces.
文摘In this investigation, an approach using Coac-tive Neuro-Fuzzy Inference System (CANFIS) as diagnosis system for breast cancer has been proposed on Wisconsin Breast Cancer Data (WBCD). It is occasionally difficult to attain the ultimate diagnosis even for medical experts due to the complexity and non-linearity of the rela-tionships between the large measured factors, which can be possibly resolved with a human like decision-making process using Artificial Intelligence (AI) algorithms. CANFIS is an AI algorithm which has the advantages of both fuzzy inference system and neural networks and can deal with ambiguous data and learn from the past data by itself. The Multi Layer Percep-tron Neural Network (MLPNN), Probabilistic Neural Network (PNN) Principal Component Analysis (PCA), Support Vector Machine (SVM) and Self Organizing Map (SOM) were also tested and benchmarked for their
