Education
B.A. Applied Mathematics, University of
California at San Diego
M.A. Applied Mathematics, UCSD
Experience Summary
Mr.
Porto is President of Natural Selection, Inc., and has been with the firm since
September, 1995. Prior to joining Natural Selection, Inc., Mr. Porto was a
Senior Principal Engineer with ORINCON Corporation (1981-1995), and has been
actively involved in signal and information processing algorithm, analysis, and
software development for over 20 years. These efforts have been in the areas of
unmanned systems course of action (COA) planning, pattern
classification/recognition, multi-hypothesis Bayesian target tracking,
multi-sensor correlation, optimal estimation, acoustic, electromagnetic, and
geoseismic wave propagation and analysis, and signal/image processing. In
addition he is a recognized expert on neural networks, and has presented
tutorials on neural networks at numerous conferences. He has headed the Office
of Naval Technology (ONT) advisory panel on neural networks and data fusion
since 1990.
Mr.
Porto has extensive experience combining signal/image processing, fuzzy logic,
neural networks and evolutionary computation in the use of acoustic, seismic
and electromagnetic signals for detection, classification, and tracking. His
studies and software engineering efforts in these fields have been presented in
journal articles, at professional meetings, and in numerous technical reports.
He
has been responsible for technical management and execution on corporate
projects including efforts in UAV control, optimal COA planning, factory
scheduling, material utilization and allocation, urban traffic control, and
signal and image processing, particularly relying on the use of evolutionary
algorithms. Mr. Porto holds a B.S. in applied mathematics from UCSD and M.A. in
applied mathematics (UCSD). He was a Co-Chair of the 1989 IEEE International
Joint Conference on Neural Networks and was the General Chair of Evolutionary
Programming VII: The Seventh Annual Conference on Evolutionary Programming,
held in San Diego in 1998. He is a charter officer of the Evolutionary
Programming Society and has been an Associate Editor of the IEEE Transactions
on Evolutionary Computation since its inception in 1997. He has also assisted
in the organization of other IEEE conferences including IEEE Conferences on
Neural Networks (IJCNN), IEEE Conferences on Evolutionary Computation (CEC),
and IEEE Ocean Engineering Society and Marine Technology Society conferences
(OCEANS), from 1995-present. Mr. Porto has served as the Information Processing
Technology Chair for IEEE OES and MTS since 1992.
Experience History
2007 - present – Automated
Optimal Workorder Scheduling System for Global Delivery Tech: Mr.
Porto is leading the design and implementation of automated scheduling software
for commercial
service industries. A service-oriented application (SOA) software
architecture is used together with an evolutionary scheduler to optimally
assign work order tasks with respect to a service company’s operational
objectives and constraints. As a side benefit it will also significantly reduce
call center operation costs.
2006 - present – UGS Sensor
System for Textron Systems: Mr. Porto is researching the
application of evolutionary agent-based systems to optimize sensor resource
allocations within Textron’s Terrain
Commander (TC2), the latest version of Textron’s Unattended Ground Sensor (UGS)
product line, developed for the US Army under the Hornet Wide Area Munitions
and Air Deliverable Acoustic Sensor (ADAS) programs. This software system will be
implemented in the form of a plug-in scenario evaluator wherein the physical
location, movements, and mixture of unattended ground sensors can be optimized
dynamically with respect to topography and platform (e.g., OPFOR) movements.
2004-2006 – J-UCAS Sensor
Analysis/Optimization for Northrop Grumman Electronic Systems: Mr.
Porto lead the development of a SSSC mission planning tool that allows rapid
tradeoff analyses of various sensor systems proposed for the J-UCAS X-47
platform and subsequent UCAS variants. This system incorporates both general
situational awareness and contact dependent aspects to allow specification of
surveillance and reconnaissance missions. The
prototype software developed under this program will demonstrate the capability
of operating one or more AUVs as remote sensing systems that can automatically
search for, prosecute, and communicate information on targets of interest in
dynamic at-sea environments. This prototype software is slated for
transition to an on-board operational system scheduled for a demonstration
within a UCAS testbed in the 2007 timeframe.
2003-2007
– Autonomous Mission Planning for Distributed AUV Assets: Mr. Porto lead the development
of evolutionary algorithms to generate courses of action (COAs) for unmanned
aerial vehicles for AFRL, Rome, N.Y. The parallel-processing software developed
under this program will demonstrate the cooperative and collaborative
capabilities of multiple AUVs in realistic simulations. Preliminary software
demonstrations conducted at the SOCOM TNT experiments at Camp Roberts, CA
proved the efficacy of these techniques for real-time COA planning for small
UAVs. This software has formed the basis for an integrated UAV control system
under investigation by the UAV Battlelab in Nevada.
2003-2005
– Tomahawk Strike Network (TSN) Analysis: Mr. Porto investigated the use of computational
intelligence techniques to recognize and classify information patterns in
electromagnetic transmissions intercepted from TSN satellite data link
transmissions (SATCOM). This project, under the direction of Johns Hopkins
University’s Applied Physics Lab (JHU/APL) and NAVAIR, assessed the vulnerability
of the TSN system with respect to these intercepts, demonstrated
state-of-the-art techniques that could be used to compromise the system, and
provided recommendations for reducing the capability of outside interests to
exploit this information.
2003-2004 – Northrop Grumman UCAR
Evolutionary Mission Manager (EMM):
Mr. Porto lead the research and development of prototype autonomous UAV
mission manager software for Northrop-Grumman’s UCAR effort. This joint
DARPA/Army project developed mission planning software for the Unmanned Combat
Aerial Rotorcraft (UCAR) program. The software generates COAs, and dynamically
adapts these task plans based upon both sensed information and data from
outside intel sources.
1999-2004
– Cruise Missile Strike and Route Planning: Mr. Porto developed novel algorithms using
evolutionary computation techniques to automate cruise missile strike planning
for NAVAIR. This system, which interfaces with the ComGlobal mission planning
software, generates optimal strike plan solutions in near-real time. Mr. Porto
lead the design and implementation efforts of all C/C++ software developed for
this project.
1998-2003
– Determination of RNA Secondary Structure: Mr. Porto designed and implemented novel software
for ISIS Corporation that uses evolutionary algorithms to determine the
secondary folding structure of RNA. This effort, potentially a first in the
pharmaceutical industry, discovers and classifies homologous structures
conserved through the process of natural evolution. The software has been
successfully tested on a number of RNA structures, and significantly
outperforms conventional industry techniques, both in quality of solutions as
well in computational time.
1999-2002 – U.S. Army Evolution
of Intelligent Behaviors:
Mr. Porto was responsible for the development of software which extends
the previous work for STRICOM to incorporate multiple personnel soft-factors
using JANUS as a simulation engine. This approach uses distributed processing
techniques to provide true real-time evolution of tactical plans for unmanned
ground vehicles. Mr. Porto was the project manager and chief architect for this
U.S. Army and National Guard training program.
1998-2002
– Evolving Interactively Intelligent Adversaries: Mr. Porto modified and extended
the automated behavior planning system designed for STRICOM to work on a
heterogeneous suite of computers for the U.S. Army at Ft. Leavenworth, Kansas.
Mr. Porto was the principal investigator and software development manager for
this project. Modifications and extensions to the previous STRICOM work include
the creation of robust communication mechanisms, object-oriented design,
advanced prediction algorithms, terrain features, and extension of the previous
system to utilize multi-player game theory. This project was managed in
conjunction with UCSD personnel in a joint STTR effort.
1998-2000
– Classification of Seismic Signals:
In support of the DARPA MEMs project, Mr. Porto designed and implemented a
novel neural-network based system to classify a range of seismic signals.
Features from these signals, first extracted using advanced signal processing
techniques, range from a single marine walking to various vehicle types. The
classification algorithm uses evolutionary computation to design and train the networks.
This system was tested with great success in the field at Camp Pendleton,
California, and greatly enhances the classification capabilities over the
current CFAR outputs.
1997-1998
– Optimal Allocation of Satellite/UAV Surveillance Resources: Mr. Porto developed software
for Rockwell/Boeing Corp. that optimally allocates satellite and unmanned
aerial vehicle as used in surveillance settings. This software uses
evolutionary techniques to temporally allocate these resources while
maintaining a complex set of constraints (slew times, image qualities,
differential- time imaging, etc.). This software outperformed the heuristic and
human methods previously used to allocate these resources. It also generates
optimal solutions for combined UAV and satellite resources that previously were
done separately.
1995-2003
– Automated Cruise Missile Strike Planner: Mr. Porto worked with JHU/APL to develop and
integrate evolutionary algorithms that optimize strike plans for cruise
missiles. Various design aspects included multiple missile types, automatic
environmental updates, temporal decision planning, coordination with
communication schedules, and complex constraint satisfaction. The software is
being used in-situ at JHU/APL and has been demonstrated to NAVAIR and at
various naval facilities. Mr. Porto was responsible for the design and
implementation efforts of all C/C++ software developed for this project.
1996-1997
– Evolving Interactively Intelligent Agents: Mr. Porto designed and implemented an automated
system that generates interactively intelligent behaviors for
computer-generated forces for the U.S. Army at STRICOM. These behaviors
interact with other computer or human-guided forces, and learn appropriate
actions in light of a constantly changing environment. He has also adapted this
software for path planning and robotic planning for NIST.
1995-1998
– Assyst, GmbH:
Mr. Porto designed, implemented, and integrated an automated marker template
(material utilization) optimization package for Assyst. The software programs
optimized the allocation of template markers for garment cutting using
evolutionary computation. Software developed for this project outperformed both
human and other optimization methods, and is currently in use at numerous Levi
Strauss cutting plants throughout the world.
1995-1996
Levi Strauss:
Mr. Porto designed an automated factory scheduling for Levi Strauss finishing
plants. This system uses evolutionary programming to optimize the temporal
allocation of various garments to a set of processing machines (dechlorinate,
stone wash, rewash, dry, etc.) in the finishing plant. This software was tested
on site at the finishing plant at Amarillo Texas, and is currently being used
to evaluate throughput for operations at several other Levi Strauss finishing
plants.
1991-1995
- Nonacoustic ASW Studies for the Office of Naval Research:
Mr. Porto studied and developed conventional and neural network
algorithms for non-acoustic ASW utilizing magnetic, thermal, and other sensors.
This work includes modeling as well as real data acquisition and analysis for
surface and subsurface target detection, classification, and tracking in
shallow water. This project involves sensor development, data processing,
neural network/conventional algorithmic designs, data fusion with other sensor
types, and tactical utilities studies. Mr. Porto was task manager of the
NN/Data Fusion research and is also a member of the ONR Nonacoustic ASW
Advisory Panel.
1988-1995
- DARPA Acoustic Nontraditional Exploitation System (DANTES): Mr. Porto’s work on the DARPA
sponsored DANTES program has included developing advanced real-time broadband
signal processing methods to extract and enhance acoustic data features for
input into successfully implemented methods and neural network topologies that
deal with a wide variety of passive nontraditional signals. Mr. Porto has participated in numerous at-sea
experiments onboard USN submarines gathering and processing data in real-time.
He has developed novel electronic circuits that modify existing commercial VCR
recording systems for storage of high bandwidth multi-channel PCM data. He has
also developed novel neural network methods to deal with active acoustic
returns from CTFM sonars for mine detection. This work involved the
construction of special control circuitry, processing software, and detection
algorithms. Mr. Porto also developed real-time software and hardware for the
multichannel PRISM signal processing and pattern classification system.
1988-1993
– Artificial Intelligence-Based Sonar Signal Processing for the Automated
Surveillance Information Processing System (ASIPS): Mr. Porto performed system
software development on Sun workstations and MicroVAXs for the ASIPS program to
develop a target detection, classification, and tracking system that employs
artificial intelligence techniques and neural networks. He adapted the advanced
neural net approaches to narrowband, broadband, and transient signal processing
that he developed under the Air Defense Initiative program described below to
use both passive and active acoustic data sources, including returns from CTFM,
monostatic, and bistatic active sonar sources. Information from these various
sources is processed, then fused by an expert system to generate higher level,
higher accuracy scenarios used in navigation and threat assessment. This
program automated many of the IUSS detection, classification, and tracking
functions that were currently operator intensive.
1990
– Multi-Static Sonar (MSS) Program: Mr. Porto supported the design, development,
and testing of real-time data driven software for the MSS program. This work included design and implementation
of sequential detectors, Kalman filter trackers, and system communications
software. This software, programmed in C and executed on a Sun computer, is
being used in sea trials on the LFA/MSS platform in real time under full Navy
operations tests.
1987-1990
– Air Defense Initiative (ADI) Submarine Signal Detection and Analysis: Mr. Porto supported the ADI
Signal Detection and Analysis Program for the Naval Ocean Systems Center
(NOSC). He was responsible for the development and application of broadband
acoustic signal processing algorithms, optimal matched filters, and graphics
software. He researched neural network approaches to the detection and
classification of nontraditional acoustic signals in real time and successfully
implemented software simulating neural networks that process real data.
1986-1987
– PICES-Software Engineering and Analysis: Mr. Porto
was heavily involved in the analysis of system requirements and the development
of the Bayesian Recursion (BAYR)-derived PICES multitarget, multisensor data
fusion/correlation algorithm for NOSC. This work included adaptation of the
BAYR code to utilize array processors, parallel processing and database
management techniques, and design and analysis of extended Kalman Filter
trackers within this code. He analyzed system performance and created measures
of performance and effectiveness (MOEs and MOPs) to measure and quantify
algorithmic throughput and efficiency.
1984-1986
– JTIDS Support and Analysis: For the NOSC Joint Tactical Information
Distribution System (JTIDS) development section, Mr. Porto performed research
and analysis of various aspects of optimal RELNAV filtering, algorithm design,
communications signal transmission, and wave propagation nonlinearities. This
included modeling and generating a computer simulation of the JTIDS system
(SCENEVAL) to develop and test RELNAV Kalman filter designs and optimize
communications system performance. The
code was designed, fully documented (PDS, PPS) and written to NAVY MIL-STD 1679
and is currently installed in the JTIDS JDES testbed at NOSC. He designed specific system test and
evaluation plans for Naval requirements of the JTIDS RELNAV function. Mr. Porto
also wrote several technical documents for this project.
1983-1985
– Undersea Noise Studies and Analysis: For the SURTASS and IUSS systems, Mr. Porto
was involved in the analysis of undersea noise data. This included analyzing the statistical
properties of ambient ocean noise, departures from Gaussianity, and the
development of revised ocean noise models based on these studies. Mr. Porto
developed special microprocessor-based signal processing algorithms to
correlate and filter the undersea background noise data.
1981-1984
– STIC Experiment Support: Mr. Porto was actively involved in numerous
real-time multitarget tracking experiments at the Acoustic Research Center (now
Surveillance Test and Integration Center (STIC)) at the Naval Ocean Systems
Center (NOSC). This work involved developing FORTRAN-based Kalman filter
tracking algorithms and surveillance displays for these experiments. Undersea data from multiple sources and radar
data were combined using data fusion techniques developed at ORINCON. He is
thoroughly familiar with the ARC computer center and its peripheral devices.
1981-1983
– Ocean Tactical Targeting:
Mr. Porto was responsible for the analysis of system requirements and coding of
joint detection/estimation search and Kalman filter tracking algorithms for a
multitarget, multisensor surveillance system. He modified and implemented a
numerical partial differential equation-solving package to simulate
multidimensional probability density functions that describe these
sensor-target scenarios. He also developed various programs using adaptive and
Kalman filters to optimize multisensor trajectory search paths using both
positive and negative information from these same sensors. Mr. Porto has
developed numerous graphic display packages designed to display two- and
three-dimensional data for multitarget, multisensor systems, tracking systems
and various signal processing applications. He is thoroughly familiar with
numerical analysis techniques, covariance analysis and optimal filter design,
and he has developed new high precision, fast multidimensional function
optimization algorithms. This work required processing and analysis of data
collected from air, surface, and subsurface Navy platforms.
1980-1981
– Geoseismic Wave Propagation Modeling:
Mr. Porto was involved in the development of a computer program to simulate and
model geoseismic wave propagation and strong ground-motion phenomena. This
required research and development of numerically stable and efficient routines
to calculate Greens Functions for heterogeneous three-dimensional earth models.
He developed and implemented various multistage signal processing techniques for
deconvolving the ground motion records to determine site-specific impulse
functions. The software was used to simulate ground motion frequency spectra
for the San Onofre and Diablo Canyon nuclear power plant sites, and results
were presented in testimony at the NRC licensing hearings.
1979-1981
– Mathematics Department: Mr. Porto was a teaching assistant for
Professor John A. Trangenstein; in Calculus, Linear Algebra, Numerical
Analysis, and Differential Equations.
1981-1983
– Electrical Engineering Department: Mr. Porto was a teaching assistant for Dr.
Vivek Samant; in Non-Linear Optimization.
1977-1980
– Math and Statistics Tutor: Mr. Porto tutored college students in all
levels of mathematics and statistics at the Learning Resources Center.
Security Clearance
Mr.
Porto was granted a (current) TOP SECRET clearance by DISCO on 2 August 1984.
Tutorials:
Oceans'99 Sept. 13, 1999 "Computational Intelligence: Theory and
Seattle,
Washington Applications in Ocean
Surveillance"
ANNIE'97 Nov. 9, 1997 "An Introduction to Evolutionary
Computation"
St. Louis, Missouri
Supercomputing'95 Dec. 4, 1995 "Genetic Algorithms and
San
Diego, California
Evolutionary
Programming"
Oceans'95 Oct. 12, 1995 "Computational Intelligence: Theory and
San
Diego, California
Applications
in Ocean Surveillance"
Oceans'93 Oct. 18, 1993 "Ocean Engineering Applications of Neural
Victoria,
B.C., Canada
Networks
and Fuzzy Systems"
Oceans'92 Oct. 26, 1992 "Neural Networks: Theory and Ocean
Newport,
Rhode Island Surveillance
Applications"
Publications:
V.W.
Porto, 2005,
" Tomahawk Strike Network (TSN) SATCOM Analysis and
Vulnerability Assessment", Final Report for NAVAIR, JHU/APL, January
2005. (classified)
Porto
VW, Fogel DB,
Fogel LJ, Fogel GB, Johnson N, and Cheung M (2005) “Classifying Sonar Returns
for the Presence of Mines: Evolving Neural Networks
and Evolving Rules,” 2005 IEEE Symposium on Computational
Intelligence for Homeland Security and Personal Safety, D.B. Fogel and V.
Piuri (eds.), IEEE Press, Piscataway, NJ, pp. 123-130.
Porto
VW, Fogel LJ,
and Fogel DB (2004) “Using Evolutionary Computation for Seismic Signal
Processing: A Homeland Security Application,” Proceedings of 2004
IEEE International Conference on Computational Intelligence for Homeland
Security and Personal Safety, IEEE Press, Venice, Italy, pp. 62-66.
Fogel
GB, Porto VW, Weekes DG, Fogel DB, Griffey RH, McNeil JA, Lesnik E,
Ecker D, and Sampath R (2002) “Discovery of RNA Structural Elements Using
Evolutionary Computation,” Nucleic Acids Research, Vol. 30:23, pp.
5310-5317.
Porto, V.W., (2000) “Evolutionary Programming.” In Evolutionary Computation 1: Basic Algorithms and Operators, T. Back, D. Fogel, T. Michalewicz (Eds), IOP Publishing.
V.
William Porto,
1999, " Using Evolutionary Programming to Optimize the Allocation of
Surveillance Assets", Simulated Evolution and Learning, B. McKay, X. Yao,
C.S. Newton, J.-H. Kim, T. Furuhashi (Eds.), Springer Verlag, LNAI, Volume
1585, Issue , pp 0215-0222.
V.William
Porto, David B.
Fogel, and Lawrence J. Fogel 1998, "Generating Novel Tactics through
Evolutionary Computation ", SIGART Bulletin, Fall 1998, ACM Press, Vol 9,
No. 2, pp. 8-14.
V.
William Porto,
1998, "Evolving Integrated Low-Level Behaviors into Intelligently
Interactive Simulated Forces", Evolutionary Programming VII, 7th Annual
Conference on Evolutionary Programming, V.W. Porto, N. Saravanan, D. Waagen,
and A.E. Eiben, eds., San Diego, CA, Berlin, Germany: Springer Verlag, pp.
781-791.
V.
William Porto,
1997, "Evolution of Intelligently Interactive Behaviors for Simulated
Forces", Evolutionary Programming VI, 6th International Conference, EP97,
Peter J. Angeline, Robert G. Reynolds, John R. McDonnell, and Russ Eberhart,
eds., Berlin, Germany: Springer Verlag, pp. 419-429.
V.
William Porto,
1997, "On the Practical Application of Evolutionary Programming to
Optimize Job Shop Scheduling", IPMM'97: Australiasia-Pacific Forum on
Intelligent Processing & Manufacturing of Materials, T. Chandra, S.R.
Leclair, J.A. Meech, B. Verma, M. Smith, B.Balachandran, eds., Brisbane,
Australia: Watson Ferguson & Co., Vol. 1, pp. 593-599.
V.
William Porto,
"Evolutionary Programming", 1997, in Handbook of Evolutionary
Computation, T. Back, D.B. Fogel, Z. Michalewicz eds., Oxford, U.K.: IOP Press
and Oxford University Press, Section B1.4.
V.
William Porto,
"Neural-Evolutionary Systems", 1997, in Handbook of Evolutionary
Computation, T. Back, D.B. Fogel, Z. Michalewicz eds., Oxford, U.K.: IOP Press
and Oxford University Press, Section D1.
V.
William Porto,
"Neural-Evolutionary Systems", 1997, Handbook of Neural Computation,
E. Fiesler and R. Beale, eds., Oxford, U.K.: IOP Press and Oxford University
Press, Section D2.
Fogel,
L.J., Porto, V.W., and Owen, M., 1996, "An Intelligently
Interactive Non-Rule-Based Computer Generated Force", Proceedings of the
6th Conference on Computer Generated Forces and Behavioral Representation,
Orlando, FL: Institute for Simulation and Training, STRICOM-DMSO, pp. 265-270.
V.
William Porto,
1995, "Non-Acoustic Sensor Array Localization using Evolutionary
Programming", Evolutionary Programming IV: Proc. of the 4th Annual
Conference on Evolutionary Programming, John R. McDonnell, Robert G. Reynolds,
and David B. Fogel, eds., Cambridge, MA, The MIT Press, pp. 19-32.
V.W.
Porto, D.B.
Fogel, and L.J. Fogel, 1995, "Alternative Neural Network Training
Methods", IEEE Expert, June 1995, Vol 10, No. 3, pp. 16-22.
V.W.
Porto, 1994,
"Array Localization using Least Squares Minimization", Proceedings of
Oceans'94, Piscataway, NJ: IEEE Press, Vol II, pp. 527-532.
V.W.
Porto, 1993,
"A method for optimal step size determination for training neural
networks", San Diego, CA, ORINCON Internal Technical Report, TR93-144.
V.W.
Porto, 1992,
"Data Fusion & Neural Network Applications", First Annual
Deployable Surveillance Systems Technology Review, Naval Air Warfare Center
Aircraft Division, April 1992, Warminster, PA: NAWC. (classified)
V.W.
Porto and D.B.
Fogel, 1992, "Neural Networks for AUV Guidance Control", Sea
Technology, Feb. 1992, Vol 33, No. 2, pp. 25-35.
V.W.
Porto, 1992,
"Alternative Methods for Training Neural Networks", 1st Annual Conf.
on Evolutionary Programming, David B. Fogel and Wirt Atmar, eds., La Jolla, CA:
Evolutionary Programming Society, pp. 100-110.
V.W.
Porto, 1990,
"Evolutionary Methods for Training Neural Networks for Underwater Pattern
Classification", 24th Annual Asilomar Conf. on Signals, Systems, and
Computers, Pacific Grove, CA, Nov. 1990, Piscataway, NJ: IEEE Press, pp.
1015-1019.
V.W.
Porto and D.B.
Fogel, 1990, "Neural Network Techniques for Navigation of AUVs",
Proc. of the Symposium on Autonomous Underwater Vehicle Technology, Wash. D.C,
June 1990, Piscataway, NJ: IEEE Press, pp. 137-141.
D.B.
Fogel, L.J. Fogel, and V.W. Porto, 1990, "Evolutionary Programming
for Training Neural Networks", IJCNN Proceedings, Piscataway, NJ: IEEE
Press, Vol. 1, pp. 601-605.
V.W.
Porto, D.B.
Fogel, and L.J. Fogel, 1990, "Evolving Neural Networks", Biological
Cybernetics, Vol 63, pp. 487-493.
V.W.
Porto, 1989,
"Detection of Undersea Objects using Neural Networks", 23rd Annual
Asilomar Conf. on Signals, Systems, and Computers, Pacific Grove, CA, Oct.
1989, Piscataway, NJ: IEEE Press, pp. 376-380.
V.W.
Porto,
1988,"Neural Network Applications in Transient Detection and
Classification", UnderSeas Defense Conference, San Diego, Oct. 1988.
(classified)
V.W.
Porto, 1988,
"Transient Detection using Neural Networks and Artificial
Intelligence", Proc. of the Submarine Technology Symposium, JHU/APL, June
1988. (classified)
Brett D.
Castille and Vincent W. Porto, 1988, "Estimation of Size and
Location of Buried Objects using Measurements Made with an Array of
Magnetometers", San Diego, CA, ORINCON Internal Technical Report, OCR 88-U-0-114.
Daniel
L. Alspach and Vincent W. Porto, 1985, "Containment Probabilities
for APT One Array Initialization SPA", San Diego, CA, ORINCON Technical
Report, TM 349.
Bill
Porto and Gerry
Anderson, 1985, "RELNAV Source Selection and Grid Acquisition on
Initialization", San Diego, CA, ORINCON Technical Report, TM 369.
Bill
Porto, 1984,
"RELNAV Performance Spec. under Poor Geometry", San Diego, CA,
ORINCON Technical Report, TM 346.
Fogel
DB, Wasson EC, Boughton EM, Porto VW, and Shively J (1997) "Initial
Results of Training Neural Networks to Detect Breast Cancer using Evolutionary
Programming," Control and
Cybernetics, vol. 26:3, pp. 497-510.
Fogel
DB, Wasson EC, Boughton EM, and Porto VW (1997) "A Step Toward
Computer-Assisted Mammography using Evolutionary Programming and Neural
Networks," Cancer Letters, Vol.
119, pp. 93-97.
Fogel
DB, Wasson EC, Boughton EM, and Porto VW (1997) "Linear and Neural
Models for Classifying Breast Cancer," IEEE
Trans. Medical Imaging.
Fogel,
DB, Wasson EC, Boughton EM, and Porto VW (1997) "Evolving
Artificial Neural Networks for Screening Features from Mammograms," Artificial Intelligence in Medicine.
Porto VW
and Fogel DB (1997) "Evolving Neural Networks," In Artificial Neural Networks: Prospects for
Medicine, R. Dybowski (ed.), Lands and Springer-Verlag, Berlin.
Fogel
DB, Fogel LJ, and Porto VW (1991) "Evolutionary Methods for
Training Neural Networks," Proc. of
Conf. on Neural Networks for Ocean
Engineering, Wash. DC, pp. 317-328.
Fogel
DB and Ghozeil A (1998) "The schema theorem and the misallocation of
trials in the presence of stochastic effects," Evolutionary Programming VII: Proc. of the 7th Ann. Conf. on
Evolutionary Programming, V.W. Porto, N. Saravanan, D.E. Waagen, and
A.E. Eiben (eds.), Springer, Berlin.
Fogel
GB, Chellapilla K, and Fogel DB (1998) "Reconstruction of DNA sequence
information from a simulated DNA chip using evolutionary programming," Evolutionary Programming VII: Proc. of the
7th Ann. Conf. on Evolutionary Programming, V.W. Porto, N. Saravanan,
D.E. Waagen, and A.E. Eiben (eds.), Springer, Berlin.
Fogel
DB, Angeline PJ, Porto VW, Wasson EC, and Boughton EM (1998) "Using
Evolutionary Computation to Learn About Detecting Breast Cancer," 1998 IEEE International Conference on
Systems, Man and Cybernetics: Data Mining and Knowledge Discovery, S.H.
Rubin (chair).
Fogel GB, Porto VW, Weekes
DG, Fogel DB, Griffey RH, McNeil JA, Lesnik E, Ecker DJ, Sampath R (2002)
"Discovery of RNA Structural Elements Using Evolutionary
Computation," Nucleic Acids Research. Vol. 30, pp 5310-5317.